CN111816297A - Cloud-based nCoV virus diagnosis and treatment system and method - Google Patents
Cloud-based nCoV virus diagnosis and treatment system and method Download PDFInfo
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- 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
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
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- G—PHYSICS
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- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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Abstract
The invention provides a cloud-based nCoV virus diagnosis and treatment system and method, which are used for acquiring patient information and various indexes and generating diagnosis suggestions at the same time by a remote diagnosis mode, reducing doctor-patient contact and effectively reducing infection risks.
Description
Technical Field
The invention relates to the technical field of electronic diagnosis and treatment, in particular to a cloud-based nCoV virus diagnosis and treatment system and method.
Background
The incubation period of 2019-nCoV pneumonia is generally 3-7 days, patients mostly suffer from fever, cough, myalgia or hypodynamia, and although the prognosis of most patients is good, part of patients can rapidly progress to ARDS and further progress to severe or critical states. Medical staff need to look after 4-5 patients on average, and the medical staff is in close contact with the patients, has great mental stress and is easy to be exhausted. By utilizing the head-mounted screen display type remote monitoring scheme, the contact between doctors and patients can be reduced, and the infection risk is effectively reduced.
Disclosure of Invention
The invention aims to provide a cloud-based nCoV diagnosis and treatment system and method, which utilize a remote monitoring scheme to reduce doctor-patient contact and effectively reduce infection risks and provide reference for doctor diagnosis through an automatic corresponding diagnosis and treatment scheme and a self-prevention and control suggestion.
In order to achieve the above object, an aspect of the present invention provides a cloud-based nCoV virus diagnosis and treatment system, including:
the patient side comprises an acquisition module, a first interaction module and a first communication module, wherein the acquisition module is used for acquiring symptom and physiological index change data of a patient, the first interaction module provides a registration page and an interaction page, the registration page is used for providing account operations such as registration and login of the patient and recording basic information of the patient, the interaction page is used for interacting illness state information with the patient, and the first communication module is used for establishing a first communication link for transmitting data with a doctor side in real time;
the doctor end comprises a data processing module, a second interaction module and a second communication module, the data processing module is used for processing physiological index change data of a patient and generating a diagnosis and treatment scheme and a self-prevention and control suggestion according to a data processing result, the second interaction module is used for interacting illness state information with the doctor, and the second communication module is used for establishing a second communication link for transmitting data with the cloud server in real time;
and the cloud server is used for receiving, transmitting and storing the symptom and physiological index change data generated by the patient end and the diagnosis and treatment scheme and self-prevention and control suggestion generated by the doctor end.
Furthermore, the acquisition module is connected with a body temperature acquisition device, a blood oxygen saturation acquisition device, a respiratory frequency acquisition device and a heart rate acquisition device;
the body temperature acquisition device acquires body temperature data of a patient;
the blood oxygen saturation degree acquisition device acquires blood oxygen saturation degree data of a patient;
the respiratory frequency acquisition device acquires respiratory frequency data of a patient;
the heart rate acquisition device acquires heart rate data of a patient.
Furthermore, the data processing module counts the physiological index change of the patient according to the body temperature data, the blood oxygen saturation degree data, the respiratory frequency data and the heart rate data of the patient to evaluate the grade of the illness state of the patient, and forms a corresponding diagnosis and treatment scheme and a self-prevention and control suggestion according to the corresponding grade.
Further, the data processing module judges the change of the physiological index of the patient, and when the change of the physiological index of the patient exceeds a normal value range or reaches an alert threshold value, the data processing module sends alarm information to the second interaction module.
Furthermore, the first interactive module and the second interactive module both comprise a head-mounted display screen, and the patient and the doctor complete the interaction of the state of an illness by wearing the head-mounted display screen.
Furthermore, the cloud server periodically performs statistical analysis on the illness state information and the physiological indexes of the patient, provides the peripheral novel coronavirus related information according to the area of the patient, and the information comprises the number of newly increased peripheral infected persons, newly increased infection sites, the accumulated number of infected persons, the information of adjacent fixed-point hospitals and the like.
On the other hand, the invention also provides a using method of the nCoV virus diagnosis and treatment system based on the cloud, which is characterized by comprising the following steps:
the patient logs in a registration page of the patient side and inputs basic information of the patient;
the patient answers the designed questions item by item through an interactive page of the patient end and feeds symptoms back to the doctor end;
the patient side acquires the symptom and physiological index change data of the patient through an acquisition module;
the doctor end generates a diagnosis and treatment scheme and a self-prevention and control suggestion according to the symptom and physiological index change data of the patient;
and the cloud server receives, transmits and stores the symptoms and the physiological index change data generated by the patient end and the diagnosis and treatment scheme and the self-prevention and control suggestion generated by the doctor end.
Further, the method further comprises:
the doctor end judges the change of the physiological indexes of the patient, and sends an alarm when the change of the physiological indexes of the patient exceeds a normal value range or reaches a warning threshold value.
Further, the method further comprises:
the cloud server periodically performs statistical analysis on the illness state information and the physiological indexes of the patient, and provides corresponding related information of the novel coronavirus in the peripheral region according to the region and the illness state level of the patient.
Further, the method further comprises:
the cloud server provides the clinical data, the guide, the article, the lecture, the related link and the like of local related experts, first-line experts and first-line working clinicians for the doctor end.
The invention provides a cloud-based nCoV virus diagnosis and treatment system and method, which are used for acquiring patient information and various indexes and generating diagnosis suggestions at the same time by a remote diagnosis mode, reducing doctor-patient contact and effectively reducing infection risks.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a system framework diagram of a cloud-based nCoV virus diagnosis and treatment system according to an embodiment of the present invention.
Fig. 2 is a frame diagram of the patient end of one embodiment of the present invention.
FIG. 3 is a frame diagram of a physician's end of one embodiment of the present invention;
FIG. 4 is a block diagram of an acquisition module according to one embodiment of the invention;
fig. 5 is a flowchart of a method for using the nCoV virus diagnosis and treatment system based on the cloud according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. A
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.
Fig. 1 is a system framework diagram of a nCoV virus diagnosis and treatment system based on a cloud terminal according to an embodiment of the present invention, and as shown in fig. 1, the nCoV virus diagnosis and treatment system based on the cloud terminal of the present invention includes a patient terminal 1, a doctor terminal 2, and a cloud server 3.
As shown in fig. 2, the patient side 1 comprises an acquisition module 101, a first interaction module 102 and a first communication module 103. The acquisition module is used for acquiring the symptom and physiological index change data of the patient. The first interaction module provides a registration page and an interaction page, the registration page is used for providing account operations such as registration and login of a patient and inputting basic information of the patient, and the interaction page is used for interacting illness state information with the patient. The first communication module is used for establishing a first communication link for transmitting data with the doctor end in real time.
In one embodiment, the registration page of the first interactive module comprises basic information of the name, sex, native place, identification number, residence location, residence and the like of the registered patient. And the patient feeds back symptoms to the doctor end by answering the designed questions item by item in the interactive page of the first interactive module.
In one embodiment, the first interaction module employs a head-mounted display screen to complete the interaction of the patient with the doctor.
In one embodiment, the first communication module 103 is in communication connection with the doctor end 2 by means of wired communication or wireless communication.
In one embodiment, the patient end 1 may also include other devices to aid in the timely discovery of common complication signs that occur during the course of a patient's trial, and/or to record the patient's trial condition. For example, a pedometer is used to record the pace, longest walking time in a single experiment, etc. of the patient.
Fig. 4 is a frame diagram of an acquisition module 101 according to an embodiment of the present invention, as shown in fig. 3, the acquisition module 101 is connected with a body temperature acquisition device 104, a finger-clipped blood oxygen saturation acquisition device 105, a respiratory rate acquisition device 106, and a heart rate acquisition device 107. Body temperature acquisition device 104 is used for gathering patient's body temperature data, and blood oxygen degree of saturation acquisition device 105 is used for gathering patient's blood oxygen degree of saturation data, and respiratory rate acquisition device 106 is used for gathering patient respiratory rate data, and heart rate acquisition device 107 is used for gathering patient's heart rate data.
Fig. 3 is a block diagram of the doctor end 2 according to an embodiment of the present invention, as shown in fig. 3, the doctor end 2 includes a data processing module 201, a second interaction module 202 and a second communication module 203. The data processing module 201 is configured to process physiological index change data of a patient, and generate a diagnosis and treatment scheme and a self-prevention and control suggestion according to a data processing result. The second interaction module 202 is configured to interact with the doctor for the illness state information, and the second communication module 203 is configured to establish a second communication link for transmitting data with the cloud server in real time.
In one embodiment, the data processing module 201 estimates the probability of infecting the patient with the new coronavirus according to the change of the physiological index of the patient through the body temperature data, the blood oxygen saturation data, the patient respiratory rate data and the patient heart rate data of the patient, and forms a corresponding diagnosis and treatment scheme and a self-prevention and control suggestion according to the infection probability.
Specifically, the infection probability is divided into three levels corresponding to three diagnosis and treatment schemes.
Wherein, when the probability reaches less than 33%, the following is automatically reported: suspicious; the diagnosis and treatment scheme is as follows: 1) reminding hand washing; 2) follow-up patient self-isolation work
The probability reaches 33% -85%, and the result is automatically reported to be suspected; the diagnosis and treatment scheme is as follows: 1) washing hands; 2) temporarily closing the examination room for disinfection treatment; 3) nucleic acid detection is required;
a probability greater than or equal to 85% automatically signals a clinical diagnosis. The diagnosis and treatment scheme is as follows: 1) reporting a request for consultation immediately; 2) washing hands; 3) temporarily closing the examination room for disinfection treatment; 4) nucleic acid detection is required.
In addition, when the data processing module 202 determines that the physiological index of the patient changes, the data processing module 2 sends alarm information to the second interaction module when the physiological index of the patient changes beyond the normal value range or reaches the warning threshold.
In one embodiment, the second interaction module 202 employs a head-mounted display screen to accomplish the interaction of the patient with the physician.
In one embodiment, the second communication module 203 is connected to the cloud server 3 by wired communication or wireless communication.
The cloud server 3 is used for receiving, transmitting and storing the symptom and physiological index change data generated by the patient end and the diagnosis and treatment scheme and self-prevention and control suggestion generated by the doctor end. In the using process, the doctor end 2 uploads the calculation result to the cloud storage 3 through the second communication module 203 so as to record and store the pathophysiological change information generated when the subject moves and assist in judging the state of an illness.
In one embodiment, the data is stored in the cloud server 3, and may also be used to perform statistical analysis on the patient's condition on a regular basis. The method can be used for analyzing based on a large number of shared samples, is beneficial to the adjustment of indexes such as the standard of the disease by researchers, and is beneficial to the establishment and the improvement of individual standards of patients of different races and ages.
Specifically, the cloud server 3 can periodically perform statistical analysis on the disease condition information and physiological indexes of the patient, and provide the peripheral novel coronavirus related information according to the area where the patient is located, wherein the information includes the number of newly-increased peripheral infected persons, newly-increased infection sites, the accumulated number of infected persons, the information of nearby fixed-point hospitals and the like.
For example, the cloud server 3 periodically performs statistical analysis on the disease information and physiological indexes of the patient, and provides information related to the novel coronavirus in the periphery of the patient according to the area where the patient is located, wherein the information includes the number of newly-increased infection people in the periphery, newly-increased infection sites, the accumulated number of infection people, information of nearby fixed-point hospitals, and the like.
The cloud server 3 may also provide the doctor with the clinical data, guidance, articles, lectures, and related links of local related experts, first-line experts, and first-line working clinicians.
Fig. 5 is a flowchart of a method for using a cloud-based nCoV virus diagnosis and treatment system according to an embodiment of the present invention. The method comprises the following steps:
s1, the user logs in. The patient logs on to the registration page of the patient side and enters basic information of the patient.
And S2, interactive question answering, wherein the patient answers the designed questions item by item through an interactive page at the patient end, and the doctor end is fed back with symptoms.
And S3, collecting indexes. The patient end collects the symptom and physiological index change data of the patient through the collection module.
And S4, assisting diagnosis, and generating a diagnosis and treatment scheme and a self-prevention and control suggestion by the doctor end according to the symptoms and physiological index change data of the patient.
And S5, cloud diagnosis and analysis, wherein the cloud server receives, transmits and stores the symptoms and the physiological index change data generated by the patient end and generates corresponding diagnosis and treatment schemes and self-prevention and control suggestions generated by the doctor end.
S6, alarming the patient, and sending alarm information to the second interactive module by the data processing module when the physiological index of the patient changes beyond the normal value range or reaches the warning threshold value in the process of judging the change of the physiological index of the patient.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides a nCoV virus system of diagnosing based on high in clouds which characterized in that includes:
the patient side comprises an acquisition module, a first interaction module and a first communication module, wherein the acquisition module is used for acquiring symptom and physiological index change data of a patient, the first interaction module provides a registration page and an interaction page, the registration page is used for providing account operations such as registration and login of the patient and recording basic information of the patient, the interaction page is used for interacting illness state information with the patient, and the first communication module is used for establishing a first communication link for transmitting data with a doctor side in real time;
the doctor end comprises a data processing module, a second interaction module and a second communication module, the data processing module is used for processing physiological index change data of a patient and generating a diagnosis and treatment scheme and a self-prevention and control suggestion according to a data processing result, the second interaction module is used for interacting illness state information with the doctor, and the second communication module is used for establishing a second communication link for transmitting data with the cloud server in real time;
and the cloud server is used for receiving, transmitting and storing the symptom and physiological index change data generated by the patient end and the diagnosis and treatment scheme and self-prevention and control suggestion generated by the doctor end.
2. The cloud-based nCoV virus diagnosis and treatment system according to claim 1, wherein the acquisition module is connected with a body temperature acquisition device, a blood oxygen saturation acquisition device, a respiratory rate acquisition device and a heart rate acquisition device;
the body temperature acquisition device acquires body temperature data of a patient;
the blood oxygen saturation degree acquisition device acquires blood oxygen saturation degree data of a patient;
the respiratory frequency acquisition device acquires respiratory frequency data of a patient;
the heart rate acquisition device acquires heart rate data of a patient.
3. The cloud-based nCoV virus diagnosis and treatment system according to claim 2, wherein the data processing module evaluates the probability of infection of the patient according to the change of the physiological index of the patient in accordance with the body temperature data, the blood oxygen saturation degree data, the respiratory rate data and the heart rate data of the patient, and forms a corresponding diagnosis and treatment scheme and a self-defense suggestion according to the corresponding probabilities.
4. The cloud-based nCoV virus diagnosis and treatment system according to claim 3, wherein the data processing module determines a change in a physiological index of the patient, and when the change in the physiological index of the patient exceeds a normal range or reaches a warning threshold, the data processing module sends an alarm message to the second interaction module.
5. The cloud-based nCoV virus diagnosis and treatment system of claim 1, wherein the first interactive module and the second interactive module each comprise a head-mounted display screen, and the patient and the doctor complete disease interaction with the head-mounted display screen.
6. The cloud-based nCoV virus diagnosis and treatment system according to claim 1, wherein the cloud server periodically performs statistical analysis on the disease condition information and physiological indexes of the patient, and provides information related to the novel coronavirus in the periphery of the patient according to the area of the patient, wherein the information includes the number of newly increased infection people in the periphery, newly increased infection sites, the accumulated number of infection people, information of nearby fixed-point hospitals, and the like.
7. Use of a cloud-based nCoV virus diagnostic and treatment system according to claims 1 to 6, comprising the steps of:
the patient logs in a registration page of the patient side and inputs basic information of the patient;
the patient answers the designed questions item by item through an interactive page of the patient end and feeds symptoms back to the doctor end;
the patient side acquires the symptom and physiological index change data of the patient through an acquisition module;
the doctor end generates a diagnosis and treatment scheme and a self-prevention and control suggestion according to the symptom and physiological index change data of the patient;
and the cloud server receives, transmits and stores the symptoms and the physiological index change data generated by the patient end and the diagnosis and treatment scheme and the self-prevention and control suggestion generated by the doctor end.
8. A method as claimed in claim 7, further comprising:
the doctor end judges the change of the physiological indexes of the patient, and sends an alarm when the change of the physiological indexes of the patient exceeds a normal value range or reaches a warning threshold value.
9. A method as claimed in claim 7, comprising:
the cloud server periodically performs statistical analysis on the illness state information and the physiological indexes of the patient, and provides corresponding related information of the novel coronavirus in the peripheral region according to the region and the illness state level of the patient.
10. A method as claimed in claim 7, further comprising:
the cloud server provides the clinical data, the guide, the article, the lecture, the related link and the like of local related experts, first-line experts and first-line working clinicians for the doctor end.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113161010A (en) * | 2021-05-14 | 2021-07-23 | 复旦大学附属中山医院 | Auxiliary diagnosis system for distinguishing common cold, influenza and new coronavirus |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2360251C1 (en) * | 2007-12-18 | 2009-06-27 | Юлия Александровна Белая | Method of probability determination of becoming infected with helicobacter pylori |
| CN102184258A (en) * | 2011-06-02 | 2011-09-14 | 中国人民解放军军事医学科学院微生物流行病研究所 | On-the-spot epidemiological information collection method based on Google Maps |
| WO2011138506A1 (en) * | 2010-05-04 | 2011-11-10 | Jari Nuutila | Flow cytometric method for distinguishing between bacterial and viral infections |
| CN103793610A (en) * | 2014-02-17 | 2014-05-14 | 复旦大学附属中山医院 | ARDS monitoring and analyzing management system based on cloud and terminal Internet of Things |
| CN104200418A (en) * | 2014-09-29 | 2014-12-10 | 北京中美联医学科学研究院有限公司 | Intelligent home diagnosis and treatment system and method based on mobile internet |
| CN106709252A (en) * | 2016-12-26 | 2017-05-24 | 重庆星空云医疗科技有限公司 | Intelligent decision-making assistance system for predicting, diagnosing, treating and controlling hospital infection |
| US20170235871A1 (en) * | 2014-08-14 | 2017-08-17 | Memed Diagnostics Ltd. | Computational analysis of biological data using manifold and a hyperplane |
| US20180078216A1 (en) * | 2016-09-16 | 2018-03-22 | Welch Allyn, Inc. | Non-Invasive Determination of Disease States |
| CN109670541A (en) * | 2018-12-07 | 2019-04-23 | 中国科学院软件研究所 | A kind of mosquito matchmaker's infectious disease fever crowd's range flags method based on spatial clustering |
| CN109903838A (en) * | 2019-02-22 | 2019-06-18 | 爱尔眼科医院集团股份有限公司 | Diabetes and diabetic retinopathy network prevent and treat system |
| CN110377847A (en) * | 2019-07-15 | 2019-10-25 | 中国人民解放军军事科学院军事医学研究院 | A kind of electronic map visualization method and system towards epidemic distribution |
| CN110875087A (en) * | 2018-09-03 | 2020-03-10 | 广州呼吸健康研究院 | Chronic lung disease management system |
-
2020
- 2020-03-31 CN CN202010246966.9A patent/CN111816297A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2360251C1 (en) * | 2007-12-18 | 2009-06-27 | Юлия Александровна Белая | Method of probability determination of becoming infected with helicobacter pylori |
| WO2011138506A1 (en) * | 2010-05-04 | 2011-11-10 | Jari Nuutila | Flow cytometric method for distinguishing between bacterial and viral infections |
| CN102184258A (en) * | 2011-06-02 | 2011-09-14 | 中国人民解放军军事医学科学院微生物流行病研究所 | On-the-spot epidemiological information collection method based on Google Maps |
| CN103793610A (en) * | 2014-02-17 | 2014-05-14 | 复旦大学附属中山医院 | ARDS monitoring and analyzing management system based on cloud and terminal Internet of Things |
| US20170235871A1 (en) * | 2014-08-14 | 2017-08-17 | Memed Diagnostics Ltd. | Computational analysis of biological data using manifold and a hyperplane |
| CN104200418A (en) * | 2014-09-29 | 2014-12-10 | 北京中美联医学科学研究院有限公司 | Intelligent home diagnosis and treatment system and method based on mobile internet |
| US20180078216A1 (en) * | 2016-09-16 | 2018-03-22 | Welch Allyn, Inc. | Non-Invasive Determination of Disease States |
| CN106709252A (en) * | 2016-12-26 | 2017-05-24 | 重庆星空云医疗科技有限公司 | Intelligent decision-making assistance system for predicting, diagnosing, treating and controlling hospital infection |
| CN110875087A (en) * | 2018-09-03 | 2020-03-10 | 广州呼吸健康研究院 | Chronic lung disease management system |
| CN109670541A (en) * | 2018-12-07 | 2019-04-23 | 中国科学院软件研究所 | A kind of mosquito matchmaker's infectious disease fever crowd's range flags method based on spatial clustering |
| CN109903838A (en) * | 2019-02-22 | 2019-06-18 | 爱尔眼科医院集团股份有限公司 | Diabetes and diabetic retinopathy network prevent and treat system |
| CN110377847A (en) * | 2019-07-15 | 2019-10-25 | 中国人民解放军军事科学院军事医学研究院 | A kind of electronic map visualization method and system towards epidemic distribution |
Cited By (1)
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|---|---|---|---|---|
| CN113161010A (en) * | 2021-05-14 | 2021-07-23 | 复旦大学附属中山医院 | Auxiliary diagnosis system for distinguishing common cold, influenza and new coronavirus |
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