RU2647159C2 - Choice of clinical guidance for cervical cancer - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: group of inventions refers to medical technology, namely to means of making clinical decisions for cervical cancer. Medical device for screening cervical cancer, contains a processor for controlling a medical device, a database of medical manuals containing a set of clinical guidelines for cervical cancer, memory for storing machine-executable instructions, while execution of the commands prompts the processor to obtain the demographic data of the survey object, obtain the data of the symptoms characterizing the survey object, reception of the data of the screening test characterizing a subject of inspection, and selecting a subset of screening guides from a set of clinical guidelines, while executing the commands further causes the processor to generate a colposcopy inspection request using a subset of screening guides, obtaining colposcopic data collected by a colposcope, and selecting a subset of colposcopy guides from a set of clinical guidelines in accordance with demographic data and colposcopic data. Computer-readable storage medium and a medical device provide a method of operating a device for screening cervical cancer.

EFFECT: use of inventions allows to expand range of means for screening cervical cancer.

15 cl, 6 dwg

Description

FIELD OF THE INVENTION

The invention relates to the support of clinical decision-making, in particular, to the selection of clinical guidelines for cervical cancer.

BACKGROUND OF THE INVENTION

Cervical cancer is the main cancer in women in India. The high incidence of this cancer is due mainly to the lack of appropriate screening. Cytological screening in the form of a Pap smear was effective in reducing the burden of disease in developed countries. However, the said screening is difficult to carry out in conditions of limited resources, for example, India or China, due to the requirements for laboratories and the need for qualified medical specialists.

Therefore, there is a need for cervical cancer screening agents that require less laboratory resources and / or qualified medical professionals.

US 2005/256745 A1 discloses a computer network comprising a first computer and at least one second computer, which are interconnected in electronics. The first computer is connected to the first medical institution and contains commands for searching and calling over the network of at least one data structure for the patient included in the medical program. At least one data structure for a patient comprises, collectively, a patient identifier, a molecular profile from a biological sample obtained from a patient in the first medical institution, and the clinical characteristics of the patient that were obtained at the first medical institution. The first computer contains commands for searching and calling through a network connection for one of a plurality of treatment regimens that appear suitable for the patient based on the molecular profile and clinical characteristics of the patient. The molecular profile obtained from the biological sample is combined with the classical clinical characteristics compiled by the patient’s physician to form the comprehensive characteristics of the medical condition the patient. The mentioned exhaustive characteristics are used to select a treatment regimen for a patient.

In addition, WO 2008/049239 A1 discloses computer systems for detecting endometrial diseases or the endometrial phase of a test subject, and measures endometrial markers or polynucleotides encoding markers in a sample from the test subject. Information corresponding to at least one of the markers is collected from the network, and, based on phenotypic information, a marker or, optionally, other markers and collected information, a determination is made whether the test subject is susceptible to in vitro fertilization, whether there is an endometrial disease or predisposition to endometrial disease, and, if desired, a procedure or treatment is recommended.

SUMMARY OF THE INVENTION

The invention provides a medical device, a method for operating a medical device, and a computer program product in the independent claims. Embodiments are provided in the dependent claims.

Embodiments of the invention may provide an improved cervical cancer screening tool by providing a medical device that is suitable for selecting a subset of screening guidelines from a set of clinical guidelines using patient demographics, symptom data, and screening test data. The medical device is further suitable for generating a request for colposcopic screening using a subset of the screening guide. The medical device is further suitable for selecting a subset of colposcopy guidelines using at least colposcopic data and patient demographics.

The term "computer-readable storage medium" in the context of this application covers any tangible storage medium that can store instructions that can be executed by a processor of a computer device. A computer-readable storage medium may be referred to as a computer-readable long-term storage medium. A computer-readable storage medium may also be called a material computer-readable storage medium. In some embodiments, a computer-readable storage medium may also store data that can be accessed by a processor of a computer device. Examples of computer-readable storage media include, but are not limited to: floppy disk, punched tape, punch cards, hard disk drives, solid state hard drives, flash memory, USB flash drives, random access memory (RAM), read-only memory (ROM), optical disk, magneto-optical disk and an array of processor registers. Examples of optical discs include compact discs (CDs) and universal digital discs (DVDs), for example, CD-ROMs (ROM on CD-ROMs), CD-RWs (rewritable CDs), CD-Rs (single-disc CDs) recording), DVD-ROM (ROM on DVDs), DVD-RW (rewritable DVDs) or DVD-R (write-once DVDs). The term computer-readable storage medium also refers to various types of recording media that can be accessed by a computer device via a network or communication channel. For example, data can be called up via modem, over the Internet, or over a local area network. Mention of a computer-readable storage medium should be interpreted as possibly multiple computer-readable storage media. Various executable components of a program or programs may be stored in different cells. A computer-readable storage medium may be, for example, several computer-readable storage media within the same computer system. A computer-readable storage medium may also be a computer-readable storage medium distributed across multiple computer systems or computer devices.

“Computer memory” or “memory” is an example of a computer-readable storage medium. Computer memory is any memory that is directly accessible to the processor. Examples of computer memory include, but are not limited to: RAM memory, registers, and register arrays. References to “computer memory” or “memory” should be interpreted as possibly to several memory blocks. The memory may be, for example, several memory units within the same computer system. The memory may also be several memory blocks distributed over several computer systems or computer devices.

A “computer storage device” or “storage device” is an example of a computer-readable storage medium. A computer storage device is any non-volatile computer-readable storage medium. Examples of computer storage devices include, but are not limited to: a hard disk drive, a USB flash drive, a floppy disk drive, a smart card, a DVD disk, a CD-ROM, and a solid state drive. In some embodiments, the computer storage device may also be computer memory, or vice versa. References to “computer storage device” or “storage device” should be interpreted as possibly to multiple storage devices or units. The storage device may, for example, be multiple storage devices within the same computer system or a single computer device. The storage device may also be several storage devices distributed across multiple computer systems or computer devices.

The term "computer device" in the context of this application covers any device containing a processor. The term "processor" in the context of the present application encompasses an electronic component that is capable of executing a program or machine-executable instruction. References to a computer device containing a “processor” should be interpreted as possibly containing at least two processors or processor cores. The processor may be, for example, a multi-core processor. A processor may also be called a collection of processors located in one computer system or distributed across several computer systems. The term computer device should also be interpreted as possibly referring to an aggregate or network of computer devices containing, each, a processor or processors. Many programs contain programs executed by several processors, which may be located within the same computer device, or which may even be distributed across several computer devices.

A “user interface” in the context of this application is an interface that enables a user or operator to interact with a computer or computer system. A "user interface" may also be called a "human-machine interface". The user interface may provide information or data to the operator and / or receive information or data from the operator. The user interface may allow operator input to be received by the computer and may provide the user with output from the computer. In other words, the user interface may provide the operator with the ability to control or manipulate the computer, and the interface may allow the computer to display the results of operator control or manipulation. Displaying data or information on a display or graphical user interface is an example of providing information to an operator. Data acquisition via keyboard, mouse, trackball, touchpad, pointing device, graphic tablet, joystick, game tablet, network video camera, headset, gear levers, steering wheel, pedals, gloves with mounting, dance mat, remote control, at least one switch of at least one button and accelerometer is, in each case, an example of user interface components that allow you to receive information or data from an opera Torah.

The term "hardware interface" in the context of this application covers an interface that provides the processor of a computer system with the ability to interact with and / or control an external computer device and / or device. The hardware interface may provide the processor with the ability to send control signals or commands to an external computer device and / or apparatus. The hardware interface may also provide the processor with the ability to communicate with an external computer device and / or device. Examples of the hardware interface include, but are not limited to: universal serial bus, IEEE 1394 port, parallel port, IEEE 1284 port, serial port, RS-232 port, IEEE-488 port, Bluetooth connection, wireless local area network connection, TCP / IP, Ethernet connection, control voltage interface, MIDI (digital musical instrument interface), analog input interface and digital input interface.

The term “display” or “display device” as used herein encompasses an output device or user interface intended for displaying images or data. The display can output visual, audio and / or tactile data. Examples of the display include, but are not limited to: a computer monitor, a television screen, a touch screen, a tactile electronic display, a braille screen, a cathode ray tube (CRT), a cathode ray tube, a bistable display, electronic paper, a vector display, a flat panel display, a vacuum fluorescent display (VF), light emitting diode (LED) displays, electroluminescent display (ELD), plasma display panels (PDP), liquid crystal display (LCD), organic light emitting diode displays diodes (OSD), projector and video helmet.

The term "database" in the context of this application covers a data file or repository that contains data that may be available to the processor. Examples of databases are, but are not limited to: a data file, a relational database, a file system folder containing data files, and a dynamic spreadsheet file.

The term “medical image data” as used herein encompasses two-, three-, or more multidimensional data that is collected using a scanner for medical imaging. A scanner for medical imaging is defined in this application as a device designed to collect information about the physical structure of the patient and to build data sets of two-dimensional or three-dimensional medical images. Medical imaging data can be used to create visualizations that are suitable for the diagnosis of a doctor. Mentioned visualization can be performed using a computer.

Histopathological data, magnetic resonance imaging data, computed tomography data and photon probe data are examples of medical image data. The term “photon probe” as used herein encompasses a diagnostic device useful for detecting cancerous tissue using an optical means. The photon probe data is data collected by the photon probe.

In the context of the present application, the term “colposcope” encompasses a low magnification microscope and a powerful light source that is used to visually examine the cervix with magnification to help diagnose cervical cancer. In some cases, the colposcope can be a stereographic and binocular field microscope. In other cases, the colposcope is a monocular microscope.

In accordance with one aspect of the invention, there is provided a medical device comprising a processor for controlling a medical device. The medical device further comprises a database of medical guidelines containing a set of clinical guidelines for cervical cancer. A database of medical guidelines, for example, can be implemented or stored in a medical device, directly selectable by a processor, or the medical device may also include a server for delivering a set of clinical guidelines upon request to the processor. The medical device further comprises a memory for storing machine-executable instructions. Execution of instructions causes the processor to obtain demographic data of the survey object. Demographic data are data that characterize the subject of the survey. Said demographic data may contain, for example, personal and / or medical information about the subject of the examination. The execution of commands additionally encourages the processor to obtain symptom data characterizing the object of examination. Symptom data in the context of this application covers data that characterize the medical condition of the subject. The execution of commands additionally encourages the processor to obtain screening test data characterizing the object of examination. Screening test data in the context of this application covers the results of a medical diagnostic test. For example, a screening test data may be, but is not limited to, the results of a Pap test or Pap test. The execution of the instructions further encourages the processor to select a subset of screening guides from the set of clinical guides according to demographic data, symptom data, and screening test data. A medical device is able to automatically select guidelines from a set of clinical guidelines that are relevant to the current medical condition of the test subject. Demographic data, symptom data, and screening data are used to select a subset of screening guides.

The execution of the instructions further prompts the processor to formulate a colposcopic examination request using a subset of screening guides. For example, a subset of screening guides may recommend colposcopic examination of the cervix. The mentioned recommendation can be used to formulate a request for colposcopic examination. The execution of the instructions further causes the processor to receive colposcopic data collected by means of the colposcope. A request is generated for colposcopic data, and then colposcopic data is collected by colposcope. The execution of the instructions further encourages the processor to select a subset of colposcopy guides from the set of clinical guides according to demographic data and colposcopic data.

A subset of colposcopy guidelines is a clinical guide relevant to specific demographic data and patient colposcopic examination results. This embodiment of the invention may be useful because demographic data and clinical guidelines are compiled for use during screening of a test subject for cervical cancer. The present invention can be useful in the process of screening objects for examination for cervical cancer and subsequent examination using a colposcope.

In another embodiment, executing instructions causes the processor to display a subset of the screening guides on the display. This feature can benefit doctors as well as other healthcare providers, such as nurses or midwives. Displaying a subset of screening guides can help guide choices or doctor actions.

In another embodiment, executing the instructions further causes the processor to send a subset of the screening guides directly to the colposcope.

In another embodiment, the execution of instructions is divided into separate places. For example, a colposcope computer and the place where symptom data is received may be separate blocks. In some embodiments, the patient’s demographic data is called up or retrieved both when choosing a subset of screening guides and when choosing a subset of colposcopy guides.

In another embodiment, the medical device comprises a colposcope. This solution can be especially useful because the screening of the test object can be controlled by a medical professional working with a colposcope. In another embodiment, the medical device is at least partially implemented in a colposcope computer.

In another embodiment, the execution of instructions causes the processor to generate commands for the colposcopic procedure using a request for colposcopic examination. The execution of the instructions further causes the processor to display the colposcopic procedure commands on the display before receiving the colposcopic data. The present embodiment can be beneficial because it can provide commands to ensure the correct colposcopic procedure. This feature can be especially useful when there is a shortage of trained medical personnel.

In another embodiment, executing the instructions further causes the processor to display a subset of the screening guides on the display.

In another embodiment, executing the instructions further prompts the processor to place a subset of the screening guides in the patient database.

In another embodiment, symptom data is obtained through a user interface. For example, a doctor or healthcare provider may enter symptom data.

In another embodiment, symptom data is obtained from a computer system or database. In such a case, symptom data can be provided, for example, by a remote patient monitoring system.

In another embodiment, demographic data is obtained from a patient database.

In another embodiment, demographic data is obtained from a patient database.

In another embodiment, demographic data is obtained from a physician. For example, a doctor may enter data from the keyboard into the user interface of a computer.

In another embodiment, demographic data is located in a patient database.

In another embodiment, the medical device comprises a database of patients. Demographic data obtained from the patient database can be placed in the patient database for later use.

In another embodiment, the device comprises a database of patients. Demographic data can be obtained from the patient database. For example, a patient database may be provided by a server.

In another embodiment, command execution prompts the processor to plan the follow-up procedure using a subset of screening guides.

In another embodiment, command execution prompts the processor to generate a set of recommendations using a subset of screening guides.

In another embodiment, command execution prompts the processor to generate a set of recommendations using a subset of screening guides.

In another embodiment, command execution prompts the processor to form a set of colposcopic test sequences from a set of recommendations.

In another embodiment, the screening test data contains the results of a Pap smear.

In another embodiment, the medical device further comprises a medical evidence database containing a set of scientific studies on cervical cancer. Executing the instructions further causes the processor to detect a pause in the selection of the screening subset. Pausing a screening subset in the context of this application is the inability of a medical device to select a subset of screening guides. This can happen, for example, when there is not enough data to select a subset of screening guides, or when critical guides that are suitable are not available.

In another embodiment, executing the instructions further causes the processor to select a subset of screening research studies from the cervical cancer research set if a pause in the selection of the screening subset is detected. A request for a colposcopic examination is formed, at least in part, using a subset of screening research studies.

In another embodiment, the execution of instructions causes the processor to display a subset of the screening research studies on the display and / or to provide a subset of the screening research studies to the healthcare provider.

In another embodiment, executing instructions further causes the processor to generate a set of test sequences from a subset of screening research studies using an artificial intelligence module. The artificial intelligence module may be, for example, an expert system and / or a neural network. The set of test sequences may contain a request for specific diagnostic tests that must be performed on the subject of the examination.

In another embodiment, the medical device further comprises a clinical case analysis database containing a set of clinical case analyzes of cervical cancer. A case study in the context of the present application is data describing a specific history of a patient suffering from cervical cancer. Clinical case analyzes can be useful for guiding the actions of a doctor or medical professional if the situations and forecasts of the patient’s further course of the disease in the analysis of the clinical case and the object of examination are similar. Command execution further encourages the processor to detect the suspension of the selection of a subset of screening research studies. Pausing the selection of a screening research subset is the inability of the scientific device (s) to correctly select the screening research subset. This can happen, for example, when there is not enough data to select a subset of screening research studies, or when there are no guidelines that are suitable. Executing the instructions further prompts the processor to select a subset of clinical case screening analyzes from a set of cervical cancer case studies if a suspension of the screening subset is detected.

A request for a colposcopic examination is generated, at least in part, using a subset of analyzes of clinical screening cases. An embodiment may be useful if there is no possibility of choosing medical guidelines or scientific research that are relevant for predicting the further course of the disease of the object being examined. A request for a colposcopic examination is generated, at least in part, using a subset of analyzes of clinical screening cases.

In another embodiment, the suspension of a selection of a screening research subset is performed if a suspension of the selection of a screening subset is detected. That is, in some embodiments, the selection of a subset of screening research studies may not be made, and instead, the selection of a subset of analyzes of clinical screening cases is directly performed.

In another embodiment, a subset of the colposcopy guidelines may also be selected, at least in part, using screening test data.

In another embodiment, colposcopic data comprises an image characterizing the cervix of the subject to be examined.

In another embodiment, executing the instructions further causes the processor to display a subset of the colposcopy guides on the display.

In another embodiment, executing the instructions further causes the processor to place the subset of colposcopy guidelines into the patient database.

In another embodiment, executing the instructions further causes the processor to plan the follow-up procedure using a subset of the colposcopy guidelines.

In another embodiment, executing instructions further causes the processor to formulate a set of recommendations using a subset of colposcopy guidelines.

In another embodiment, the execution of instructions further causes the processor to generate a test sequence of medical imaging from a set of recommendations.

In another embodiment, executing the instructions further causes the processor to diagnose using a subset of the colposcopy guidelines.

In another embodiment, executing the instructions further causes the processor to generate a medical imaging request using a subset of the colposcopy guidelines. The request for a medical image may include a request for medical imaging performed by a medical imaging device. Examples of medical imaging devices include, but are not limited to, a magnetic resonance imaging system, a computed tomography system, and an ultrasound diagnostic system.

In another embodiment, executing the instructions further causes the processor to obtain medical image data characterizing the subject of examination. The execution of the instructions further causes the processor to select a subset of medical images from the set of clinical guidelines in accordance with the medical image data. Medical image data can be used to select a set of clinical guidelines that are relevant. The above task can be performed, for example, by an expert system and / or a neural network system.

In another embodiment, a subset of medical images may also be selected based on: demographic data, symptom data, screening test data and / or colposcopic data.

In another embodiment, executing instructions further causes the processor to display a subset of the medical manuals on the display.

In another embodiment, a subset of medical image guides is located in a patient database.

In another embodiment, executing instructions further causes the processor to generate a set of recommendations using a subset of medical images.

In another embodiment, executing instructions further causes the processor to detect a paused selection of a subset of medical images. Pausing the selection of a subset of medical images in the context of this application includes the inability of the system to select a subset of medical images. This can happen, for example, when there is not enough data to select a subset of medical images, or when there are no manuals that are suitable.

The execution of the instructions further encourages the processor to select a subset of scientific research on medical images from a set of scientific research on cervical cancer, if it is found that the selection of a subset of medical images is stopped. The present embodiment may comprise a set of scientific studies on cervical cancer. The choice of a subset of medical imaging research studies can be used as an alternative if clinical guidelines are not available, or it is not clear which clinical guidelines are applicable.

In another embodiment, executing the instructions further causes the processor to display a subset of the research on medical images on the display and / or to provide a subset of the research on medical images to a medical professional.

Command execution further encourages the processor to make a diagnosis using a subset of scientific research on medical images.

In another embodiment, the execution of the instructions further causes the processor to detect a pause in the selection of a subset of scientific imaging studies. Pausing the selection of a subset of scientific research on medical images is the inability of the system to select a subset of scientific research on medical images. This can happen, for example, when there is not enough data to select a subset of scientific research on medical images, or when critical guidelines that are appropriate are not available.

The execution of the instructions further encourages the processor to select a subset of clinical case analyzes of medical images from a set of analyzes of clinical cases of cervical cancer if a suspension of the selection of the screening subset is detected. The present embodiment may comprise a set of analyzes of clinical cases of cervical cancer.

In another embodiment, the suspension of the selection of a subset of medical image research studies is performed if a suspension of the selection of a subset of medical images is detected.

In another embodiment, executing instructions causes the processor to formulate a treatment plan using a subset of clinical case analyzes of medical images and / or a subset of medical image research studies.

In another embodiment, the medical image data comprises any of the following data: histopathological data, magnetic resonance imaging data, computed tomography data, photon probe data, and combinations thereof.

In another embodiment, the medical device further comprises a treatment plan database comprising a set of treatment plans. The execution of the instructions further causes the processor to select a treatment plan from a set of treatment plans in accordance with a subset of medical images.

In another embodiment, a treatment plan is developed based on or selected using a subset of medical images, a subset of scientific research on medical images, and / or a subset of clinical case analyzes of medical images.

In another embodiment, executing instructions further causes the processor to detect a colposcopic subset selection pause. Pausing a colposcopic subset selection is the system’s inability to select a subset of colposcopy guidelines. This can happen, for example, when there is not enough data to select a subset of colposcopy guides, or when there are no critical guides that are suitable.

The execution of the instructions further encourages the processor to select a subset of colposcopic examinations from the set of scientific studies on cervical cancer if a suspension of the choice of colposcopic subset is detected. A request for medical imaging is generated, at least in part, using a subset of colposcopic scientific studies. The above approach may be useful because scientific research can be used to generate data that is useful for the instructions of a doctor if there are no suitable guidelines.

In another embodiment, executing the instructions further causes the processor to display a subset of colposcopic scientific studies on the display and / or to provide a subset of colposcopic scientific studies to a medical professional.

In another embodiment, executing the instructions further causes the processor to detect a pause in the selection of a subset of colposcopic scientific studies. Pausing the selection of a colposcopic scientific research is the inability of the system to select a subset of colposcopic scientific research. This can happen, for example, when there is not enough data to select a subset of colposcopic scientific studies, or when critical guidelines that are suitable are not available.

The execution of the instructions further encourages the processor to select a subset of clinical case studies of colposcopy from a set of clinical case analyzes of cervical cancer if a suspension of the selection of the screening subset is detected. A request for medical imaging is generated, at least in part, using a subset of analyzes of clinical colposcopy cases.

In another embodiment, the suspension of the selection of a subset of colposcopic scientific studies is performed if a suspension of the selection of a colposcopic subset is detected.

In accordance with another aspect, the invention provides a method of operating a medical device. The medical device contains a database of medical guidelines containing a set of clinical guidelines for cervical cancer. The method comprises the step of obtaining demographic data of the surveyed subject. The method further comprises the step of obtaining these symptoms characterizing the object of examination. The method further comprises the step of obtaining screening test data characterizing the subject of examination. The method further comprises the step of selecting a subset of screening guides from the set of clinical guides in accordance with demographic data, symptom data, and screening test data. The method further comprises the step of generating a request for colposcopic examination using a subset of screening guides. The method further comprises the step of obtaining colposcopic data collected by a colposcope. The method further comprises the step of selecting a subset of colposcopy guidelines from the set of clinical guidelines in accordance with demographic data and colposcopic data.

In accordance with another aspect, the invention provides a computer program product comprising computer-executable instructions for a processor controlling a medical device. Machine-executable instructions may be stored on a long-term machine-readable storage medium. The medical device contains a database of medical guidelines containing a set of clinical guidelines for cervical cancer. Execution of instructions causes the processor to obtain demographic data of the survey object. The execution of commands additionally encourages the processor to obtain symptom data characterizing the object of examination. The execution of commands additionally encourages the processor to obtain screening test data characterizing the object of examination. The execution of the instructions further encourages the processor to select a subset of screening guides from the set of clinical guides according to demographic data, symptom data, and screening test data. The execution of the instructions further prompts the processor to formulate a request for colposcopic examination using a subset of screening guides. The execution of the instructions further causes the processor to receive colposcopic data collected by the colposcope. The execution of the instructions further encourages the processor to select a subset of colposcopy guides from the set of clinical guides according to demographic data and colposcopic data.

BRIEF DESCRIPTION OF THE DRAWINGS

The following is a description of preferred embodiments of the invention, by way of example only and with reference to the drawings, in which:

FIG. 1 is a flowchart of a method in accordance with an embodiment of the invention;

FIG. 2 is an example of a medical device in accordance with an embodiment of the invention;

FIG. 3 is an example of a medical device in accordance with a further embodiment of the invention;

FIG. 4 is a functional diagram of a clinical decision support decision implemented by an embodiment of the invention;

FIG. 5 is a flowchart that depicts the building blocks of a clinical decision support system; and

FIG. 6 is a schematic illustration of a medical device in accordance with a further embodiment of the invention.

DETAILED DESCRIPTION OF EMBODIMENTS

Elements with the same position numbers in the figures are either equivalent elements or perform the same function. Elements that are explained earlier will not necessarily be explained in the following figures, if their function is equivalent.

In FIG. 1 is a flowchart illustrating a method in accordance with an embodiment of the invention. First, at step 100, demographic data is obtained from the survey subject. Then, at step 102, symptom data characterizing the test subject is obtained. Then, at step 104, screening test data is obtained that characterizes the test subject. At step 106, a subset of the screening guides is selected from the set of clinical guidelines according to demographic data, symptom data, and screening test data. Then, at step 108, a request for colposcopic examination is generated using a subset of the screening guides. At step 109, colposcopic data collected by the colposcope is obtained. Finally, at step 110, a colposcopic subset of clinical guidelines is selected using demographic data and colposcopic data.

In FIG. 2 shows an example of a medical device 200 in accordance with an embodiment of the invention. The medical device 200 comprises a computer 202. Computer 202 includes a processor 204 that is connected to a hardware interface 206, a user interface 210, a computer storage device 212, and computer memory 214. The hardware interface 206 is optionally connected to a colposcope 208. Computer 202 is shown connected to a server 216, which, via a network or other connection, is capable of delivering the contents of the medical guide database 218 to a processor 204. Computer 202 is additionally shown connected to an analytical instrument 220. naliticheskoe device 220 may provide data 222 screening test. Data from 222 screening tests may be the results of medical tests performed on a sample from the subject.

Computer storage device 212 is depicted containing screening test data 222 that is obtained from analytic device 220. Computer storage device 212 is further shown containing demographic data 230. In some cases, demographic data 230 may be obtained from another server that contains a patient or medical database documentation. Computer storage device 212 is further shown containing symptom data 232. Symptom data 232 can also be obtained from an external database, or, in some embodiments, can also be obtained from user interface 210. For example, a doctor or other healthcare provider can enter symptom data.

Computer storage device 212 is further depicted containing a subset of screening guides. The screening guide subset is a collection of medical guidelines selected from a database of 218 medical guidelines. Computer storage device 212 is further shown containing a request for colposcopic examination. Request 236 for colposcopic examination is formed in accordance with a subset of 234 screening guides. Computer storage device 212 is further depicted containing a subset of 238 colposcopy guides. A subset of 238 colposcopy guides is a set of medical guides selected from a database of 218 medical guides in accordance with the results of colposcopic data 235.

Computer memory 214 is shown comprising a control module. The control module comprises computer-executable code for controlling the operation and function of the medical device 200. Computer memory 214 is further illustrated with a module 242 for selecting a subset of screening guides. The screening guide subset selection module 242 contains machine-executable code for selecting a screening guide subset based on the symptom data 232, the demographic data 230, and the screening test data 222. The module for selecting a subset of screening guidelines may be, for example, an expert system and / or a neural network system. Computer memory 214 is shown further comprising a colposcopic examination request generation module. The colposcopic examination request generation module 244 contains a computer-executable code for generating a colposcopic examination request 236 based on a subset of 234 screening guides. Computer memory 214 is further illustrated with a module 246 for selecting a subset of colposcopy manuals. The colposcopy guidelines subset selection module 246 contains computer-executable code for the colposcopy guidelines subset 238 using demographic data 230 and colposcopy data 235.

In FIG. 3 illustrates an embodiment of a medical device 300 in accordance with the invention. The embodiment of FIG. 3 is similar to the embodiment of FIG. 2. In addition to the features shown in FIG. 2, computer 202 in the embodiment of FIG. 3 is connected to a server 302 that is designed to provide a medical evidence database 304 to a processor 204. Computer 202 is further connected to a server 306 that is configured to provide a clinical case analysis database to a processor 204. Computer 202 is further connected to a server 307, which configured to provide a database of 309 treatment plans to the processor 204.

Computer storage device 212 is further shown comprising colposcopy instructions 310. Colposcopy teams 310 are commands that can be displayed using a user interface, such as user interface 210. For example, computer storage device 212 is further shown containing a medical imaging request 312. Computer storage device 212 is further shown containing medical image data 314. Computer storage device 212 is further depicted comprising a subset of 316 medical images of medical manuals selected from a database of medical manuals 218. Computer storage device 212 is further shown comprising a treatment plan 318.

Computer memory is further shown comprising a colposcopy instruction module 330. Colposcopy instruction module 330 comprises machine-executable code for generating colposcopy instructions 310 using a colposcopy examination request 236.

Computer memory 214 is further depicted comprising a medical imaging request module 232. The medical imaging request module 232 comprises a machine-executable code for generating a medical imaging request 312 using a subset of 238 colposcopy guides. Computer memory 214 is further shown comprising a module 334 for selecting a subset of medical images. Module 334 select a subset of medical images contains a machine-executable code that allows the processor 204 to generate a subset of medical images manuals using data 314 medical images and a database of 218 manuals. Computer memory 214 is further depicted comprising a treatment plan selection module 336. The treatment plan selection module 336 contains a machine-executable code that allows the processor 204 to select a treatment plan 318 from a database 309 of treatment plans and a subset of 316 medical images. Computer memory is further shown comprising a research selection module and a clinical case analysis selection module 340. Research module 338 is a machine-executable code that allows processor 204 to examine a medical evidence database 304 and generate replacements for medical manuals. Computer memory 214 is also shown containing a clinical case analysis selection module 340, which contains machine-executable code and allows processor 204 to use the clinical case analysis database also to replace medical manuals that are not available.

In FIG. 4 is a functional diagram of a clinical decision support decision implemented by an embodiment of the invention. The clinical decision support decision is used at several levels or stages of the system. In general, the clinical decision support system can go through the following steps: the system can collect 400 data, analyze 402 data, interpret 404 data, and finally provide 406 data for use by a medical professional. At a data collection step 400, various data is collected. At step 402, information is searched on content among demographic data, symptoms, and signs. Then, during the interpretation, clinical guidelines and / or demonstrative reasoning are applied. And finally, at presentation level 406, data, recommendations, follow-up medical observations, schedules, memos, and consultation suggestions are provided.

An embodiment of the invention, for example, the implementation of FIG. 4, can provide a simple and expedited immediate screening test based on cervical cytology. The result can be obtained using automatic sample preparation and artificial intelligence for automatic cell identification. However, many clinical conditions can lead to similar morphological features during cervical cytology. The mentioned feature leads to changes in the sensitivity and specificity of the tests. At a subsequent stage in the workflow, colposcopic examination and / or biopsy may also be necessary, which also has similar problems.

With an increase in the incidence of cervical cancer and an increase in the need for optimized therapy, there is a need for systems that accelerate the sequence of work operations, while providing the health worker with additional checks to improve the quality of screening diagnostics and therapy. Therefore, the solution to the aforementioned problem can be an integrated clinical decision support system (CDS system), autonomous or integrated into a medical device to provide guidance for different medical workers at different stages of observation in order to avoid erroneous diagnosis and treatment.

As mentioned above, cervical cancer is the most common cancer in women in India. For a successful fight against cervical cancer, a possible useful solution would be the systematic collection, archiving of data (obtained using several means, for example, Pap smear, HPV test (human papillomavirus), colposcopes, genomic information, visual examination using the VIA method , MRI for brachytherapy, etc.), analysis and presentation of data in a unified and intuitive way to support the clinician in making the right decision on effective treatment and subsequent medical supervision. The present disclosure proposes a comprehensive clinical decision support system for problems encountered in modern technology. Embodiments of the invention may provide a system that collects data, makes it possible to request data, simulates clinical case analyzes, and provides interpretation support. The system can also provide support for follow-up medical supervision of the patient, form memos and provide the possibility of planning and implementing therapy, in combination with clinical guidelines.

In some embodiments, a subsequent screening test is performed, either in the form of cervical cytology, or in the form of an HPV test, or visual inspection. In the present case, there are guidelines for deciding the next step in each individual case (for example, ASCCP 2006 guidelines).

Even a test subject with a negative test result must pass the test after a certain period of time to retest. This may require an effective callback mechanism. If the patient population is large and the medical resources are insufficient, then a very effective system would be helpful. Similarly, there are clinical guidelines for managing decision-making after colposcopy and treatment procedures. These options depend on the age of the woman, the presence of childbirth in the anamnesis, clinical stage, concomitant diseases, etc. These parameters make the manuals very specific for a particular case, and also difficult to remember for the clinician.

The lack of qualified clinicians at different stages of observation can lead to errors in the diagnosis of the disease, which means a missed opportunity to treat cervical cancer. The latter then leads to an increase in the incidence of cervical cancer and, consequently, to an increase in the burden of cervical cancer. At each stage of observation, an accurate interpretation is required, which also depends on the conclusions made at the previous stages in sequentially working operations. Since different participants are present at each stage of the observation, there is a possibility of an erroneous diagnosis due to loss of information or inadequate information.

Embodiments of the invention can not only keep patient information on individual medical cases at different stages, but also streamline the sequence of work operations and provide support for clinical decision-making. Thus, the above possibilities can increase the accuracy and reliability of monitoring cervical cancer.

Embodiments of the invention may provide a comprehensive solution for monitoring cervical cancer. This clinical decision support decision (CDS decision) may be based on at least one of the following: patient demographics; signs and symptoms; clinical interpretation based on visual examination using the methods of VI / VIA / VIAM and / or HPV test; morphological features obtained from cytological images taken from a Pap smear test; clinical observations made on colposcopic images; clinical interpretation of images obtained by other imaging tools, such as computed tomography (CT) or magnetic resonance imaging (MRI), and clinical observations based on biopsy. The above action can be performed while providing guidance on the relevant next steps of the action, using the available clinical guidelines, as an indicative treatment. In FIG. 4 shows the building blocks of one embodiment of a CDS solution.

In FIG. 5 is a flowchart that depicts the building blocks of a clinical decision support system. At block 500, data is collected. The data may include patient demographics, signs, symptoms, clinical information from screening and / or diagnosis, and / or imaging. The next step is block 502, which is a clinical decision support machine. This unit may operate based on clinical guidelines and / or clinical indications. And finally, block 504 is a data representation. The presentation of the data may contain recommendations, procedures for subsequent medical follow-up, preparation of plans, leaflets, consulting and / or planning data that can be presented to the medical professional.

In some embodiments, the data collection module collects diverse information, for example: patient demographic data, signs and symptoms (text information), and screening and diagnostic results (visual / video information).

In some embodiments, a clinical decision support machine (CDS machine) processes information using evidence-based reasoning and several clinical guidelines (IFCPC (World Organization for Colposcopy), NCCN (National Cancer Cancer Network), ASCCP (American Society for Colposcopy and pathology of the cervix), etc.) that are contained in the aforementioned machine.

In some embodiments, the data presentation module provides recommendations, advice, treatment planning, memos, and the like.

In some embodiments, there is a two-stage CDS machine that provides recommendations at two different levels, i.e. screening and diagnosis. In some embodiments, the implementation of the CDS machine includes a manual execution machine and a reading machine.

In some embodiments, implementation, the user is presented with similar cases when there are no manuals or indications.

In some embodiments, the proposed CDS system is closely related to the sequence of operations for cervical cancer.

A detailed block diagram of an embodiment of a CDS system is shown in FIG. 6. This system is closely related to the sequence of work steps for monitoring cervical cancer. In FIG. 6 illustrates an example of a medical device 600 or clinical decision making system in accordance with an embodiment of the invention. The clinical decision making system depicted in FIG. 6 contains a first CDS machine 602, a second CDS machine 604, and a third CDS machine 606. Each of the clinical decision support machines 602, 604, 606 is connected to a clinical decision support database 608 and a patient demographic database 610. Clinical decision support database 608 can provide, for example, clinical guidelines, cervical cancer clinical guidelines, a cervical cancer research kit, and a clinical case analysis database containing a clinical case analysis kit for cervical cancer.

The first clinical decision support machine 602 receives screening test data 612. Clinical Decision Support Machine 1 602 uses the screening test data 612 and information from the Clinical Decision Support Database 608 and the patient demographic database 610 to form interpretations and recommendations 614. These recommendations may include scheduling or re-screening the test subject 616, or the recommendations mentioned may require a colposcopic examination. If this is the case, then the results of 618 colposcopic examinations are then entered into the machine 2 604 support clinical decision-making. Clinical Decision Support Machine 2 604 uses databases 608 and 610 to create guidance 620 on classification and biopsy. Biopsy results 622 are then fed to a clinical decision support machine 3 606, which then uses a patient demographic database 610 and / or a clinical guide database 608 along with magnetic resonance images 624 and 626 NCCN and / or ICMR (Institute of Cytology and Oncological Prevention) to formulate a treatment plan 628. After treatment 628, system 600 may provide recommendations 630 and / or plan follow-up medical follow-ups of the test subject.

In some embodiments, the input to both CDS machines is patient demographics, main complaints, signs and symptoms.

The patient’s demographic data may include the patient’s age, the nature of her menstrual cycles, her sexual history, and whether the patient has already reached menopause.

Signs and symptoms may include the presence of a discharge of any kind. If there is any discharge, then it can be described as: a cheesy white discharge, a greenish discharge with a foul odor, bloody discharge and an ulcer, etc.

CDS-machine 1 can provide input from screening tools, for example, analysis of a Pap smear (which includes normal, candidal, with vaginal trichomonas, inflammatory, reactive, ASCUS (squamous atypia of uncertain significance), LSIL (low-grade precancer), HSIL (high precancer), SCC (expression of tumor markers) and HPV (human papillomavirus)) and the result of the study according to the VIA method.

The CDS machine 2 can receive input for cancer severity from diagnostic tools such as colposcopes. The input contains an acetone indicator, the presence of mosaics, punctuation and atypical vessels. Input data can be entered into the system manually or can be selected automatically.

In some embodiments, implementation, the CDS machine 1 and the machine 2 are independent machines. Each machine contains two components: a manual execution machine and a testimony machine.

In this embodiment, the guidance machine performs the steps of the guidelines based on patient data and input from screening and / or diagnostic tools. Guides are implemented using GLIF / GLEE. The above tool internalizes all the information that is required to support clinical decision making. The information is specific to this clinical manual, and this means that if several manuals are adopted, these manuals will be executed as separate server modules that interact with general patient information. Each manual execution machine has a “normal” as well as a “limited” mode of operation, with the latter mode indicating a situation in which the manual refers to an aspect that is peripheral to the current clinical case. The choice of a decision regarding the mode of application of this manual is up to the clinician.

In some embodiments, the implementation of the test machine is initialized when the manuals are fuzzy or not available for decision. Indications are entered into decision making using existing medical databases. The test machine may also provide similar cases where there are no manuals or indications.

The CDS machine 1 compiles the input from the patient’s demographic data and the screening test data in accordance with the clinical guidelines and the evidence-based reasoning for interpretation. Based on the interpretation of the manual, the machine generates a set of recommendations, for example, the need for subsequent medical supervision (when, for what, etc. to observe) or the need for an additional diagnostic test, for example, colposcopy. If the recommendation is an additional colposcopic examination, then the CDS machine 2 can be activated, which receives input from colposcopic examinations. The machine also compiles the results of colposcopy and patient demographics in accordance with the guidelines for classifying cancer severity and recommends additional tests and / or biopsy.

After the diagnosis is made according to the results of colposcopy, a biopsy and determination of the stage of the disease can be performed by histopathology, MRI and / or CT imaging. Then follow a treatment plan based on the NCCN or ICMR guidelines. These guidelines also take into account the patient’s demographic data, the state of concomitant diseases, etc., which makes the decision-making process that involves many medical specialties complex. The CDS machine 3 may use the above information from the various sources listed above to offer appropriate treatment and options for subsequent medical follow-up, taking into account the medical approach based on the guidelines and indications.

The above invention is presented in detail in the drawings and set forth in the description, however, the above images and description should be considered illustrative or exemplary, and not limiting; those. the invention is not limited to the disclosed embodiments.

Specialists in the art, after studying the drawings, the disclosure and the attached claims, can find and implement other modifications of the disclosed embodiments in the process of practical application of the claimed invention. In the claims, the expression “comprising” does not exclude other elements or steps, the singular in the form of an indefinite article does not exclude the plural. A single processor or other unit may fulfill the functions of several elements listed in the claims. The obvious fact that some features are mentioned in mutually different dependent dependent claims does not mean that it is not possible to use a combination of these features in a suitable case. The computer program may be stored / distributed on a suitable medium, for example, an optical data medium or a semiconductor medium, supplied together with or included in other hardware, but may also be distributed in other forms, for example, via the Internet or other wired or wireless telecommunications systems. No position in the claims can be considered limiting the scope of the invention.

LIST OF POSITIONS

200 medical device

202 computer

204 processor

206 hardware interface

208 colposcope

210 user interface

212 computer storage device

214 computer memory

216 server

218 medical manuals database

220 analytical device

222 screening test data

230 demographic data

232 symptom data

234 subset of screening guides

236 request for colposcopic examination

235 colposcopic data

238 subset of colposcopy guides

240 control module

242 screening guides subset selection module

244 colposcopic examination request generation module

246 colposcopy guidelines subset selection module

300 medical device

302 server

304 medical evidence database

306 server

307 server

308 clinical case analysis database

309 treatment plan database

310 colposcopy teams

312 medical imaging requests

314 medical image data

316 subset of medical images

318 treatment plan

330 colposcopy team module

332 medical imaging request module

334 medical image subset selection module

336 treatment plan selection module

338 research module

340 case analysis selection module

600 medical device

602 Clinical Decision Support Machine 1

604 Clinical Decision Support Machine 2

606 Clinical Decision Support Machine 3

608 clinical decision support database

610 patient demographic database

612 screening test data

614 interpretations and recommendations

616 schedule re-screening

618 colposcopy results

620 classification and biopsy referral

622 biopsy

624 magnetic resonance imaging (MRI) and computed tomography (CT)

626 leadership of the NCCN (National Universal Cancer Network) and ICMR (Institute of Cytology and Oncology Prevention)

628 treatment

630 recommendations and / or subsequent medical supervision.

Claims (59)

1. A medical device (200, 300, 600) for screening for cervical cancer, comprising: - a processor (204) for controlling the medical device; - a database (218, 608) of medical manuals containing a set of clinical guidelines for cervical cancer; - memory (214) for storing machine-executable instructions, while executing instructions prompts the processor to: - receiving (100) demographic data (230) of the survey object; - receiving (102) data (232) of symptoms characterizing the object of examination; - obtaining (104) the data (222) of the screening test characterizing the object of examination; and - selecting (106) a subset (234) of screening guides from a set of clinical guides in accordance with demographic, symptom, and screening test data; characterized in that the execution of the instructions further induces the processor to: - generating (108) a request (236) for colposcopic examination using a subset of screening guides; - receiving (109) colposcopic data (235) collected by colposcope; and - selecting (110) a subset (238) of colposcopy guidelines from a set of clinical guidelines in accordance with demographic and colposcopic data. 2. The medical device according to claim 1, wherein the medical device comprises a colposcope (208). 3. The medical device according to claim 2, in which the execution of commands additionally prompts the processor to: - the formation of the team (310) colposcopic procedure using the request for colposcopic examination; and - displaying the colposcopic procedure command on the display (210) before receiving the colposcopic data. 4. The medical device according to claim 1, in which the medical device further comprises a database (304) of medical indications containing a set of scientific research on cervical cancer, while the execution of the instructions further induces the processor to: - detecting the suspension of the selection of the screening subset; - selecting a subset of screening research studies from a set of cervical cancer research, if a suspension of the screening subset is detected, and a request for colposcopic examination is generated, at least in part, using a subset of screening research studies. 5. The medical device according to claim 4, in which the medical device further comprises a database (308) of clinical case analyzes containing a set of analyzes of clinical cases of cervical cancer, the execution of the instructions further induces the processor to: - detecting a suspension of the selection of a subset of screening research studies; and - selecting a subset of clinical case screening analyzes from a set of cervical cancer clinical cases if a suspension of the screening subset is detected, and a colposcopic examination request is generated, at least in part, using a subset of screening clinical case analyzes. 6. The medical device according to claim 1, wherein the execution of the instructions further causes the processor to generate a request for medical imaging using a subset of colposcopy manuals. 7. The medical device according to claim 6, in which the medical device further comprises a database (304) of medical indications containing a set of scientific research on cervical cancer, the execution of the instructions further induces the processor to: - detecting a suspension of colposcopic subset selection; and - selecting a subset of colposcopic scientific research from a set of scientific research on cervical cancer, if a suspension of the choice of colposcopic subset is detected, and a request for medical imaging is generated, at least in part, using a subset of colposcopic scientific research. 8. The medical device according to claim 7, in which the medical device further comprises a database (308) of clinical case analyzes containing a set of analyzes of clinical cases of cervical cancer, the execution of the commands further induces the processor to: - detecting the suspension of the selection of a subset of colposcopic scientific research; and - selecting a subset of analyzes of clinical cases of colposcopy from a set of analyzes of clinical cases of cancer of the cervix uteri, if a suspension of the choice of a screening subset is detected, and a request for medical imaging is generated, at least in part, using a subset of analyzes of clinical cases of colposcopy. 9. The medical device according to claim 6, in which the execution of commands additionally prompts the processor to: - obtaining data (624) of the medical image characterizing the object of examination; - selecting a subset (316) of medical images from the set of clinical guidelines in accordance with the medical image data. 10. The medical device according to claim 9, in which the medical device further comprises a database (304) of medical indications containing a set of scientific research on cervical cancer, the execution of the instructions further induces the processor to - detecting the suspension of the selection of a subset of medical images; and - selecting a subset of scientific research on medical images from a set of scientific research on cervical cancer, if it is found that the selection of a subset of medical images has been suspended. 11. The medical device according to claim 10, in which the medical device further comprises a database (308) of clinical case analyzes containing a set of analyzes of clinical cases of cervical cancer, the execution of the commands further induces the processor to: - detecting the suspension of the selection of a subset of scientific research on medical images; and - selecting a subset of clinical case analyzes of medical images from a set of analyzes of clinical cases of cervical cancer, if a suspension of the selection of a screening subset is detected. 12. The medical device according to claim 9, in which the medical image data contains any of the following data: histopathological data, magnetic resonance imaging data, computed tomography data, photon probe data, and combinations thereof. 13. The medical device according to claim 9, in which the medical device further comprises a database of treatment plans containing a set of treatment plans, the execution of commands prompts the processor to select a treatment plan from the set of treatment plans in accordance with a subset of medical images. 14. The method of operation of a medical device (200, 300, 600) for screening for cervical cancer, in which the specified medical device contains a database (218, 608) of medical manuals containing a set of clinical guidelines for cervical cancer, the method comprising the following steps : - receive (100) demographic data (230) of the survey object; - receive (102) data (232) of symptoms characterizing the object of examination; - receive (104) the data (222) of the screening test characterizing the object of examination; and - select (106) a subset (234) of screening guides from the set of clinical guidelines in accordance with demographic data, symptom data, and screening test data; characterized in that - form (108) a request (236) for colposcopic examination using a subset of screening guides; - receive (109) colposcopic data (235) collected by colposcope; and - select (110) a subset (238) of colposcopy guides from the set of clinical guides in accordance with demographic data and colposcopic data. 15. A computer-readable storage medium containing machine-executable instructions (240, 242, 244, 246, 330, 332, 334, 336, 338, 340) for a processor (204) controlling a medical device (200, 300, 600) for screening cervical cancer, while the specified medical device contains a database (218, 608) of medical manuals containing a set of clinical guidelines for cervical cancer, and the execution of commands prompts the processor to: - receiving (100) demographic data (230) of the survey object; - receiving (102) data (232) of symptoms characterizing the object of examination; - obtaining (104) the data (222) of the screening test characterizing the object of examination; and - selecting (106) a subset (234) of screening guides from a set of clinical guides in accordance with demographic, symptom, and screening test data; characterized in that the execution of the instructions further induces the processor to: - generating (108) a request (236) for colposcopic examination using a subset of screening guides; - receiving (109) colposcopic data (235) collected by colposcope; and - selecting (110) a subset (238) of colposcopy guidelines from a set of clinical guidelines in accordance with demographic and colposcopic data.

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