CN112133424A - Learning diagnosis and treatment system for orthopedics department - Google Patents
Learning diagnosis and treatment system for orthopedics department Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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Abstract
The invention discloses a learning diagnosis and treatment system for orthopedics, which comprises: data acquisition device, intelligent analysis device, data storage device, suggestion device and interactive installation. The data acquisition device is used for acquiring basic information of a patient, related diagnosis and treatment information and medical data; the intelligent analysis device is used for structuring the basic information and the related diagnosis and treatment information of the patients and generating corresponding structured case information for each patient; the system is used for mining and analyzing medical data and constructing an orthopedics knowledge graph; the data storage device is used for storing the structured case information and the orthopedics knowledge map; the prompting device is used for performing combined analysis on the structured case information and the orthopedics knowledge graph and sending diagnosis and treatment suggestions according to analysis results; the interaction device is used for data interaction between the external equipment and the data storage device. The study diagnosis and treatment system provided by the invention realizes the integration of data integration, diagnosis and treatment, education and scientific research, and is high in efficiency and easy to popularize.
Description
Technical Field
The invention belongs to the technical field of artificial intelligence, and particularly relates to an intelligent learning diagnosis and treatment system for orthopedics.
Background
In the prior art, orthopedic related data acquisition is mainly completed by handwriting, electronic edition or cloud entry and other modes. Because no uniform system is used for data processing, a large amount of collected data cannot be directly applied or cannot be integrally applied at all. In addition, the scattered arrangement of a plurality of data acquisition devices and systems not only wastes the cost, but also wastes mass data. If the data can be integrated and applied, the development of orthopedics can be well promoted.
At present, the clinical diagnosis and treatment of orthopedics is mainly based on the experience of doctors, has strong subjectivity and can not realize standardized diagnosis and treatment. This results in areas with relatively poor medical conditions and low doctor levels where clinicians are unable to obtain effective medical decision support and patients are unable to obtain effective medical care. If the homogenization and standardized diagnosis and treatment of the orthopedic diseases can be realized, the cure rate of the whole orthopedic diseases and the experience of patients are undoubtedly improved.
The existing way for doctors to learn is mainly through clinical practice, and others include: the mode of attending a conference, attending a learning class, entering repair and watching on-line teaching, etc. This may lead to the situation that the content that the doctor wants to learn or needs to check the missing and fill up cannot be learned in time, and it is difficult to quickly and conveniently acquire the relevant knowledge in the clinical work.
Scientific research is usually conducted on the basis of medical data and image data of patients in departments. Due to the reasons that data cannot be shared and the like, the standard multi-center scientific research is difficult to realize at present.
Therefore, there is an urgent need for a learning diagnosis and treatment system for orthopedics that can realize mass data sharing, can provide standardized diagnosis and treatment guidance, and can assist doctors in learning and scientific research.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a multi-bit integrated learning diagnosis and treatment system for orthopedics, which integrates data sharing, diagnosis and treatment, learning and scientific research.
According to an aspect of the present invention, there is provided a learning diagnosis system for orthopedics, including: the system comprises a data acquisition device, an intelligent analysis device, a data storage device, a prompt device and an interaction device;
the data acquisition device is used for acquiring basic information of a patient, related diagnosis and treatment information and medical data;
the intelligent analysis device is used for structuring the basic information and the related diagnosis and treatment information of the patients and generating corresponding structured case information for each patient; the system is used for mining and analyzing the medical data and constructing an orthopedics knowledge graph;
the data storage device is used for storing the structured case information and the orthopedics knowledge graph;
the prompting device is used for performing combined analysis on the structured case information and the orthopedics knowledge graph and sending diagnosis and treatment suggestions according to analysis results;
and the interaction device is used for data interaction between external equipment and the data storage device.
According to an embodiment of the invention, the prompting device is further configured to perform combined analysis on the structured case information and the orthopedics knowledge graph, and send prompting information according to the analysis result.
According to another specific embodiment of the present invention, the prompt message includes: prompting a doctor to enter further diagnosis and treatment information and/or prompting a patient to update and enter basic information.
According to another embodiment of the present invention, the diagnosis and/or treatment advice and/or prompt information is sent by system message, short message, mail and/or WeChat.
According to another embodiment of the present invention, the learning diagnosis and treatment system further comprises: an external data access device;
the external data access device is used for accessing external data and performing structural processing on the accessed data to generate structural external data;
the data storage device is also used for storing the structured external data.
According to another embodiment of the present invention, the learning diagnosis and treatment system further comprises: a verification device;
the verification device is used for verifying the external equipment and giving authorization to the external equipment passing the verification;
and the interaction device is used for data interaction between the authorized external equipment and the data storage device.
According to another specific embodiment of the present invention, the intelligent analysis device uses an NER entity naming recognition + relationship extraction algorithm to mine and analyze the medical data, and constructs an orthopedic knowledge graph.
According to another specific embodiment of the present invention, the data collected by the data collecting device includes: text, pictures, audio, and/or video.
The learning diagnosis and treatment system for orthopedics provided by the invention realizes modularized rapid data entry by using intelligent equipment in the diagnosis and treatment process of orthopedic diseases; the system can guide doctors to carry out standardized and pathized clinical diagnosis and treatment, and reckoning and providing individualized treatment suggestions and cautions of the orthopedics department through a built-in complete knowledge structure; by arranging rich knowledge points, system education including diagnosis thinking, operation technology and other clinical diagnosis and treatment can be performed on doctors; and provides data, methods and platforms required by personal scientific research and multi-center scientific research.
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Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
fig. 1 is a schematic structural diagram illustrating an embodiment of a learning diagnosis and treatment system for orthopedics according to the present invention.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
Referring to fig. 1, the present invention provides a learning diagnosis and treatment system for orthopedics. The study diagnosis and treatment system comprises: the system comprises a data acquisition device 10, an intelligent analysis device 20, a data storage device 30, a prompt device 40 and an interaction device 50.
The data acquisition device 10 is used for acquiring basic information of a patient, relevant diagnosis and treatment information and medical data. Preferably, the basic information of the patient includes, but is not limited to: personal data, past medical history, allergy history and/or complaints. The basic information of the patient is used as an important reference material in diagnosis and treatment, and is necessary for the patient to see a doctor.
The related medical information may be content related to the patient's visit entered by the doctor. Such as: the results of the inquiry, more detailed description of the disease, the results of the preliminary diagnosis, the examination to be performed, and the follow-up precautions.
Sources of medical data include, but are not limited to: a large body of medical literature, such as: medical books, treatises, periodicals, academic conference materials, and the like; and a vast amount of medical case resources.
The data collected by the data collection device 10 include, but are not limited to: text, pictures, audio, and/or video. It can be understood that the basic information of the patient and the related diagnosis and treatment information in the traditional sense are mostly in the form of texts and pictures (such as X-ray films, nuclear magnetic resonance films, B-mode ultrasound images, etc.), but with the development of science and technology, a large amount of audio/video data resources appear. Especially in orthopedics, sometimes the motor morphology of a patient can directly reflect the affected part and degree; in addition, the contrast image data before and after the operation of the patient is also important for evaluating the operation condition and the rehabilitation condition of the patient. Similarly, various forms of data exist in a huge amount of medical data.
In order to improve the information utilization rate and reduce the difficulty of information processing, the intelligent analysis device 20 is configured to structure the basic information and the relevant diagnosis and treatment information of the patient, and generate corresponding structured case information for each patient. Structured case information is more convenient to store and utilize.
Furthermore, in order to reduce the difficulty of structuring information, the data acquisition device 10 may directly acquire the structured data, where conditions allow. For example: the basic information of the patient is acquired in a single-selection or multi-selection mode. The patient need only select the content to be answered, for example: gender, age, allergic medications, and the like. However, in reality, most of the data cannot be directly acquired in a structured manner, and therefore the intelligent analysis device 20 is also required to process the data.
The intelligent analysis device 20 is further configured to mine and analyze the medical data, and construct an orthopedic knowledge map. Preferably, the intelligent analysis device 20 uses natural language processing technology to perform named entity recognition + entity relationship analysis on the medical data, and extract medical entities and relationships between these entities. Wherein the entities include: disease name, surgery name, medical device name, drug name, etc.; the relationship includes: the relationship of disease to drugs, disease to surgery, surgery to medical devices, and the like. Further, the intelligent analysis device 20 performs mining and analysis on the medical data by using an NER entity naming and identifying + relationship extracting algorithm, and constructs an orthopedic knowledge map.
The data storage device 30 is used for storing the structured case information and the orthopedics knowledge map.
And the prompting device 40 is used for performing combined analysis on the structured case information and the orthopedics knowledge graph and sending diagnosis and treatment suggestions according to analysis results. Depending on the patient's stage of interrogation, the clinical recommendations may vary, for example: the clinic recommendations of the outpatient may be the name of the disease and the corresponding treatment; the diagnosis and treatment advice of the inpatient can be in-hospital examination, treatment plan, and/or discharge time, etc.; the medical advice of the patient to be operated may be: surgical scheduling, preoperative precautions, postoperative care knowledge, and the like.
In addition, the prompting device 40 is further configured to perform a combined analysis on the structured case information and the orthopedic knowledge map, and send a prompting message according to an analysis result. Preferably, the prompt message includes: prompting a doctor to enter further diagnosis and treatment information and/or prompting a patient to update and enter basic information. For example: when the structured case information shows that the patient needs to do a certain examination, the patient is prompted to input an examination result; when the structured case information shows that the operation is about to be performed, the doctor is prompted to perform preoperative preparation and the like. In addition, when abnormal values (such as hyperglycemia, hypopigmentation, etc.) exist in the structured case information, the prompting device 40 also prompts, which is beneficial for the doctor to take corresponding preventive measures for the clinical risk corresponding to the abnormal values.
The diagnosis and treatment suggestions and/or the prompt information are sent by adopting a system message, a short message, an email and/or a WeChat mode. With the rapid development of instant messaging tools such as WeChat, the prompting device 40 preferably sends diagnosis and/or prompt information in a system message and WeChat message synchronous mode.
The interaction device 50 is used for data interaction between an external device and the data storage device 30. The data interaction is mainly used for medical related people such as doctors to learn medical knowledge. For example, a doctor can log in the learning diagnosis and treatment system through a self-owned terminal, and access the data storage device 30 to learn the medical knowledge stored therein. Such learning includes not only retrieval learning of massive medical resources but also research on relevant case information. The data storage device 30 stores the case information and the orthopedic knowledge map after structuring, so that the content is rich and the utilization rate is high, and the retrieval, the query and the understanding are easy.
In order to enhance the safety of the data, preferably, the learning diagnosis and treatment system further includes: the authentication device 70. The authentication device 70 is configured to authenticate an external device, and give authorization to the external device that has been authenticated. Preferably, the external device includes: various terminals with the functions of playing characters, pictures and videos, such as computers, tablets, mobile phones and the like.
In general, an authorized external device may query and call internal data of the data storage device 30 through the interaction device 50; but cannot modify, delete, etc. the data. In practical application, if an operator of an external device has a question, suggestion, or the like about data inside the data storage device 30, the corresponding data can be labeled, and the data cannot be directly modified.
In order to further enhance the learning function of the learning diagnosis and treatment system, the learning diagnosis and treatment system further comprises: an external data access device 60. The external data access device 60 is used for accessing external data and performing structural processing on the accessed data to generate structural external data; the data storage device 30 is further configured to store the structured external data.
External data here refers to some medical systems that include rich orthopedic knowledge, common in the industry. For example: a medical orthopedic education platform. The data has high credibility, can realize data sharing after being accessed into the learning diagnosis and treatment system, and provides richer and better learning resources for people applying the system.
It can be seen that the learning diagnosis and treatment system not only contains a large amount of data, but also has rich data content, and relates to various aspects of orthopedics, especially, a large amount of structured case information is a very important and precious data resource. Scientific research personnel can log in the system under the condition of obtaining authorization, and carry out high-efficiency scientific research activities by taking the system as a platform. The learning diagnosis and treatment system is an orthopedic universal system, so that multi-center combined scientific research can be realized.
The learning diagnosis and treatment system provided by the invention combines orthopedics data entry, clinical standard diagnosis and treatment, doctor education and scientific research into a four-in-one body. The data acquisition device realizes intelligent acquisition of orthopedic data, and is convenient and fast. Both doctors and patients can enter information according to their own authority, so the data acquisition time in the invention is shortened 3/4 compared with the prior art. The data acquisition which can be carried out in real time ensures the timeliness and the accuracy of the data.
The prompting device can give a pathized diagnosis and treatment suggestion by comprehensively analyzing the structured case information and the orthopedic knowledge map, so that the orthopedic diseases are scientifically and normatively treated, and subjective errors possibly occurring to doctors in medical work are reduced. The prompting device can give reasonable diagnosis and treatment opinions and related cautions, can effectively improve the scientificity of clinical diagnosis and treatment, and avoids or even reduces the occurrence of complications.
The data acquisition device can timely make up for the lack of knowledge of diagnosis and treatment information by acquiring medical data (big data); in addition, through interaction with external data (such as a medical only orthopedics education website), learning opportunities can be provided for authorized people. The authorized population is not limited to doctors, nurses, medical students, etc. Greatly increasing the learning efficiency of the taught population, accelerating the growth of the doctor and providing a one-stop working and learning platform for the doctor.
In addition, the learning verisimilitude system can design and implement single-center and multi-center research of orthopedics on the basis of data, and can greatly improve the scientific research efficiency by analyzing the data.
Although the present invention has been described in detail with respect to the exemplary embodiments and advantages thereof, it should be understood that various changes, substitutions, and alterations can be made hereto without departing from the spirit and scope of the invention as defined by the appended claims. For other examples, one of ordinary skill in the art will readily appreciate that the order of the process steps may be varied while maintaining the scope of the present invention.
Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the disclosure of the present invention, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed, that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized according to the present invention. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.
Claims (8)
1. A learning diagnosis system for orthopedics, comprising: the system comprises a data acquisition device, an intelligent analysis device, a data storage device, a prompt device and an interaction device;
the data acquisition device is used for acquiring basic information of a patient, related diagnosis and treatment information and medical data;
the intelligent analysis device is used for structuring the basic information and the related diagnosis and treatment information of the patients and generating corresponding structured case information for each patient; the system is used for mining and analyzing the medical data and constructing an orthopedics knowledge graph;
the data storage device is used for storing the structured case information and the orthopedics knowledge graph;
the prompting device is used for performing combined analysis on the structured case information and the orthopedics knowledge graph and sending diagnosis and treatment suggestions according to analysis results;
and the interaction device is used for data interaction between external equipment and the data storage device.
2. The system of claim 1, wherein the prompting device is further configured to perform a combined analysis on the structured case information and the orthopedic knowledge map, and send a prompting message according to the analysis result.
3. The learning diagnosis and treatment system according to claim 2, wherein the prompt message includes: prompting a doctor to enter further diagnosis and treatment information and/or prompting a patient to update and enter basic information.
4. The learning diagnosis and treatment system according to claim 3, wherein the diagnosis and treatment advice and/or prompt information is sent by system message, SMS, E-mail and/or WeChat.
5. The learning clinical system of claim 4, further comprising: an external data access device;
the external data access device is used for accessing external data and performing structural processing on the accessed data to generate structural external data;
the data storage device is also used for storing the structured external data.
6. The learning clinical system of claim 5, further comprising: a verification device;
the verification device is used for verifying the external equipment and giving authorization to the external equipment passing the verification;
and the interaction device is used for data interaction between the authorized external equipment and the data storage device.
7. The learning diagnosis and treatment system according to claim 6, wherein the intelligent analysis device adopts an NER entity naming recognition + relationship extraction algorithm to mine and analyze the medical data and construct an orthopedics knowledge graph.
8. The learning diagnosis and treatment system according to claim 7, wherein the data collected by the data collection device includes: text, pictures, audio, and/or video.
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| CN202010954124.9A CN112133424A (en) | 2020-09-11 | 2020-09-11 | Learning diagnosis and treatment system for orthopedics department |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112650860A (en) * | 2021-01-15 | 2021-04-13 | 科技谷（厦门）信息技术有限公司 | Intelligent electronic medical record retrieval system based on knowledge graph |
| CN118412081A (en) * | 2024-04-24 | 2024-07-30 | 南通爆发力网络科技有限公司 | Medical data auxiliary analysis device based on artificial intelligence and operation method |
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| WO2001069513A2 (en) * | 2000-03-10 | 2001-09-20 | David S Zakim | A system and method for obtaining, processing and evaluating patient information for diagnosing disease and selecting treatment |
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| CN112650860A (en) * | 2021-01-15 | 2021-04-13 | 科技谷（厦门）信息技术有限公司 | Intelligent electronic medical record retrieval system based on knowledge graph |
| CN118412081A (en) * | 2024-04-24 | 2024-07-30 | 南通爆发力网络科技有限公司 | Medical data auxiliary analysis device based on artificial intelligence and operation method |
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