WO2024025489A1 - Health status analysis system on historical data - Google Patents

Health status analysis system on historical data Download PDF

Info

Publication number
WO2024025489A1
WO2024025489A1 PCT/TR2022/051022 TR2022051022W WO2024025489A1 WO 2024025489 A1 WO2024025489 A1 WO 2024025489A1 TR 2022051022 W TR2022051022 W TR 2022051022W WO 2024025489 A1 WO2024025489 A1 WO 2024025489A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
artificial intelligence
module
health status
historical data
Prior art date
Application number
PCT/TR2022/051022
Other languages
French (fr)
Inventor
Mustafa TUNAY
Turgay KARALİNÇ
Abdulsamet HAŞILOĞLU
Ali ÇETİNKAYA
Original Assignee
İstanbul Geli̇şi̇m Üni̇versi̇tesi̇
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by İstanbul Geli̇şi̇m Üni̇versi̇tesi̇ filed Critical İstanbul Geli̇şi̇m Üni̇versi̇tesi̇
Publication of WO2024025489A1 publication Critical patent/WO2024025489A1/en

Links

Classifications

    • 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
    • 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • 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
    • 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
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • This invention relates to a health status analysis system based on artificial intelligence, which enables early diagnosis, diagnosis and treatment planning by enabling the determination of future health status over past health data.
  • the invention in the application CN114188015 titled “Artificial Intelligence-Based Brain Stroke Disease Prediction Method and Device” is related to the technical fields of biology, medicine, and medical devices, and in particular to a method and device for predicting stroke disease based on artificial intelligence.
  • the invention in the application CN109377470 titled “Heart Disease Risk Prediction System” it is about an artificial intelligence method that analyzes the probability of heart disease from examination data such as ultrasound images and electrocardiograms.
  • This invention is a health status analysis system based on historical data, and its feature is; It allows early diagnosis and treatment planning, minimizes the need for qualified health personnel with a wide coverage area, reduces dependence on knowledge and experience, ensures equal treatment for every patient and disease, reduces loss of life and property, has a high accuracy rate, and a high error rate. It is a simple artificial intelligence-based, dynamic new technology that provides coordination and cooperation among healthcare personnel, prevents loss of time.
  • the invention in order to realize all the objectives mentioned above and which will emerge from the detailed description below; With the monitoring and follow-up of the historical data of the patients, any disease, organ, etc. It considers a highly sensitive, highly accurate system that allows to make a comprehensive prediction about the future health status of the patient without being limited to.
  • the system that is the subject of the invention minimizes the need for qualified personnel due to the increasing need for health and eliminates the need for knowledge and experience for accurate diagnosis and treatment planning.
  • the system that is the subject of the invention as a result of the analyzes made through the artificial intelligence system, important data to guide the health personnel are obtained. In this way, it is aimed to achieve correct results with minimum workload and workforce.
  • the system that is the subject of the invention automatically calculates the disease and risk ratio within the historical data of the users, without the need for prioritization according to the severity of the patient or the disease, or without requiring the patients to come for a regular check-up and presents these data to the expert. This allows for undetected situations not to be overlooked, or for detecting diseases that could not be detected at the beginning, at the right time.
  • the system which is the subject of the invention, provides a wide database of examinations and expert opinions of many patients, and presents a dynamic estimation system with low margin of error, comprehensive, low cost and not creating unnecessary workload.
  • the subject of the invention is the system; family health centers, private and public hospitals, polyclinics, etc. it can be integrated into health institutions daily, monthly, yearly, etc. it allows disease prediction to be performed on a certain scale.
  • the invention Unlimited Mobile Terminal (1) patients and their expert opinions regarding the data continuously updated and developed, equipped with data from the database (3) where historical data is transmitted continuously, the artificial intelligence Module (4), the most accurate prediction model for the creation of the patients, the analysis of data taken from the system and the Central Hospital of previous diseases such as artificial intelligence Module (4) that as a result of the transfer processes using artificial intelligence algorithms to the training module (4.1), it includes the prediction module (4.2), which works in sync with the training module (4.1) and has an up-to-date prediction model created using artificial intelligence algorithms.
  • the invention includes a database (3) an unlimited mobile terminal (1) a dynamic training module (4.1) where each incoming new data is constantly transferred.
  • the invention includes a training module (4.1) that allows each new data transferred to be continuously trained in order to create a model with high sensitivity and accuracy.
  • the invention includes the prediction module (4.2), which allows the results of the disease and risk status to be obtained with the prediction model with the highest accuracy.
  • the invention is characterized by the fact that it contains a prediction module (4.2) that allows the transfer of outcome data related to the disease and risk status to the corresponding mobile terminal (1) for viewing by medical personnel.
  • a prediction module (4.2) that allows the transfer of outcome data related to the disease and risk status to the corresponding mobile terminal (1) for viewing by medical personnel.
  • the invention includes the artificial intelligence module (4), which includes the mobile terminal (1), the network (2), the database (3), the training module (4.1) and the prediction module (4.2).
  • the invention includes a mobile terminal (1), including a phone and / or a tablet and / or a computer and / or a television and / or a portable device, etc., for medical personnel to access the system and access the result data.
  • a mobile terminal (1) including a phone and / or a tablet and / or a computer and / or a television and / or a portable device, etc., for medical personnel to access the system and access the result data.
  • the invention includes network (2) to provide data exchange between numerous mobile terminals (1) and database (3).
  • the invention includes a network (2) to provide data exchange between numerous mobile terminals (1) and the prediction module (4.2) in the artificial intelligence module (4).
  • the network (2) in the invention includes various connection types such as wired, wireless communication connections or fiber optic cables.
  • the artificial intelligence module (4) in the invention includes a training module (4.1) and a prediction module (4.2).
  • Historical data is continuously retrieved from the unlimited mobile terminal (1) to the artificial intelligence module (4) included in the invention, from the database (3), which is equipped with continuously updated and developed data regarding patients and expert opinions.
  • the data transferred from the database (3) to the artificial intelligence module (4) are transferred to the training module (4.1) in order to create the prediction models with the highest accuracy.
  • the training module (4.1) prediction models with the highest accuracy are created by processing data using different artificial intelligence algorithms.
  • each new data coming from the database (3) unlimited mobile terminal (1) is continuously transferred to a dynamic training module (4.1).
  • Each new data transferred to the training module (4.1) is continuously trained to create a model with high precision and accuracy.
  • estimation is performed with the current estimation model created by using different artificial intelligence algorithms in the prediction module (4.2), which works synchronized with the training module (4.1).
  • the result data of the disease and risk status obtained with the prediction model with the highest accuracy rate created in the prediction module (4.2) are transferred from the prediction module (4.2) to the relevant mobile terminal (1) for the health personnel to view.

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Pathology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Epidemiology (AREA)
  • Physics & Mathematics (AREA)
  • Veterinary Medicine (AREA)
  • General Physics & Mathematics (AREA)
  • Computational Linguistics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Surgery (AREA)
  • Molecular Biology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Biophysics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

This invention; It is related to the health status analysis system based on artificial intelligence, which enables early diagnosis and treatment planning by allowing the determination of future health status over past health data, and its feature is; artificial intelligence module (4), in which historical data is continuously transferred from the unlimited mobile terminal (1) from the database (3) equipped with continuously updated and developed data on patients and expert opinions, the training module (4.1), which operates using artificial intelligence algorithms, as a result of transferring data such as patient analysis and previous diseases from the central hospital system to the artificial intelligence module (4) in order to create the most accurate prediction model, it includes a prediction module (4.2) that works in sync with the training module (4.1) and has an up-to-date prediction model created using artificial intelligence algorithms.

Description

HEALTH STATUS ANALYSIS SYSTEM ON HISTORICAL DATA
Technical Field:
This invention relates to a health status analysis system based on artificial intelligence, which enables early diagnosis, diagnosis and treatment planning by enabling the determination of future health status over past health data.
State of the Art:
Today, the increasing need for health all over the world for various reasons can cause the necessary efficiency to be obtained from health services. The great increase in the need for health makes it difficult to provide the right health service by a qualified health personnel at the right time.
It is vital to benefit from health services at the right time. In particular, early diagnosis and treatment planning in this direction and implementation at the right time prevents the progression of diseases and increases survival rates. This situation is of great importance especially for the diagnosis and treatment of diseases that progress secretly and are usually diagnosed in the last stages of the disease.
In the current system, due to the global crises such as the pandemic, the need for a qualified workforce has arisen in the face of increasing health needs. At the same time, with the increasing need for health, it is necessary to give priority to various diseases and patients. Since this process delays the benefit of health services according to the priority status of the patients, it causes late diagnosis and intervention of the disease and causes loss of life and property. In addition, there is a psychological wear and tear of both health personnel and patients. Due to such deficiencies in the current system, ignoring some diseases may cause diseases to be detected late at home. Detection of diseases in late stages also makes it difficult to get positive effects from treatment. In the current system, various symptoms, anamnesis (patient history) and clinical examination data, etc. After the evaluation of the disease, diagnosis and treatment planning is carried out. However, the fact that these findings do not directly correspond to any disease at the beginning or that prodromal symptoms that do not occur directly in the organs related to the disease may mislead the health personnel. This situation causes health problems to occur in the late periods and these problems are unpredictable. For this reason, it is important to collect all the findings and monitor them in a wide scope within a certain period of time in terms of making the right diagnosis and treatment planning at the right time.
The invention in the application CN114188015 titled “Artificial Intelligence-Based Brain Stroke Disease Prediction Method and Device” is related to the technical fields of biology, medicine, and medical devices, and in particular to a method and device for predicting stroke disease based on artificial intelligence.
The invention in the application CN109377470 titled “Heart Disease Risk Prediction System” it is about an artificial intelligence method that analyzes the probability of heart disease from examination data such as ultrasound images and electrocardiograms.
The existing systems listed above do not provide a comprehensive method as they are limited to a single disease type.
As a result, it is aimed to approach every patient and disease equally, which can overcome the disadvantages mentioned above and enable early diagnosis and treatment planning, minimize the need for a qualified health personnel with a wide scope, reduce dependence on knowledge and experience, reduce loss of life and property, There is a need for an artificial intelligence-based, dynamic new technology that provides high accuracy, low error rate, high sensitivity, provides coordination and cooperation among healthcare personnel, prevents loss of time, has a simple, minimal workload and workforce. Description of the Invention:
This invention is a health status analysis system based on historical data, and its feature is; It allows early diagnosis and treatment planning, minimizes the need for qualified health personnel with a wide coverage area, reduces dependence on knowledge and experience, ensures equal treatment for every patient and disease, reduces loss of life and property, has a high accuracy rate, and a high error rate. It is a simple artificial intelligence-based, dynamic new technology that provides coordination and cooperation among healthcare personnel, prevents loss of time.
The invention in order to realize all the objectives mentioned above and which will emerge from the detailed description below; With the monitoring and follow-up of the historical data of the patients, any disease, organ, etc. It considers a highly sensitive, highly accurate system that allows to make a comprehensive prediction about the future health status of the patient without being limited to.
The system that is the subject of the invention minimizes the need for qualified personnel due to the increasing need for health and eliminates the need for knowledge and experience for accurate diagnosis and treatment planning.
Invention, blood, urine etc. analysis results; MRI, tomography, x-ray etc. medical imaging data, etc. It predicts the diseases and risks that may arise in the coming years as a result of processing the past health data of the users, especially the users, through artificial intelligence algorithms, and provides diagnosis and diagnosis in the early stages and accordingly, the application of the right treatment at the appropriate time.
In the system that is the subject of the invention, as a result of the analyzes made through the artificial intelligence system, important data to guide the health personnel are obtained. In this way, it is aimed to achieve correct results with minimum workload and workforce. The system that is the subject of the invention automatically calculates the disease and risk ratio within the historical data of the users, without the need for prioritization according to the severity of the patient or the disease, or without requiring the patients to come for a regular check-up and presents these data to the expert. This allows for undetected situations not to be overlooked, or for detecting diseases that could not be detected at the beginning, at the right time.
The system, which is the subject of the invention, provides a wide database of examinations and expert opinions of many patients, and presents a dynamic estimation system with low margin of error, comprehensive, low cost and not creating unnecessary workload.
The subject of the invention is the system; family health centers, private and public hospitals, polyclinics, etc. it can be integrated into health institutions daily, monthly, yearly, etc. it allows disease prediction to be performed on a certain scale.
Invention, the structural and characteristic features and all advantages of the product in question will be understood more clearly thanks to the figures given below and the detailed explanation written by making reference to these figures, and therefore the evaluation should be made by considering these figures and detailed explanation.
Description of the Figures:
The invention will be described with reference to the accompanying figures, so that the features of the invention will be more clearly understood and appreciated, but the purpose of this is not to limit the invention to these certain regulations. On the contrary, it is intended to cover all alternatives, changes and equivalences that can be included in the area of the invention defined by the accompanying claims. The details shown should be understood that they are shown only for the purpose of describing the preferred embodiments of the present invention and are presented in order to provide the most convenient and easily understandable description of both the shaping of methods and the rules and conceptual features of the invention. In these drawings. Figure 1 The subject of the invention is a view of the hardware that provides the functioning of the health status analysis system over the past data.
The figures to help understand the present invention are numbered as indicated in the attached image and are given below along with their names.
Description of References:
1. Mobile Terminal
2. Network
3. Database
4. Artificial Intelligence Module
4.1.Training Module
4.2.Prediction Module
Description of The Invention:
The invention, Unlimited Mobile Terminal (1) patients and their expert opinions regarding the data continuously updated and developed, equipped with data from the database (3) where historical data is transmitted continuously, the artificial intelligence Module (4), the most accurate prediction model for the creation of the patients, the analysis of data taken from the system and the Central Hospital of previous diseases such as artificial intelligence Module (4) that as a result of the transfer processes using artificial intelligence algorithms to the training module (4.1), it includes the prediction module (4.2), which works in sync with the training module (4.1) and has an up-to-date prediction model created using artificial intelligence algorithms.
The invention includes a database (3) an unlimited mobile terminal (1) a dynamic training module (4.1) where each incoming new data is constantly transferred.
The invention includes a training module (4.1) that allows each new data transferred to be continuously trained in order to create a model with high sensitivity and accuracy. The invention includes the prediction module (4.2), which allows the results of the disease and risk status to be obtained with the prediction model with the highest accuracy.
The invention is characterized by the fact that it contains a prediction module (4.2) that allows the transfer of outcome data related to the disease and risk status to the corresponding mobile terminal (1) for viewing by medical personnel.
Detailed Description of The Invention:
The invention includes the artificial intelligence module (4), which includes the mobile terminal (1), the network (2), the database (3), the training module (4.1) and the prediction module (4.2).
The invention includes a mobile terminal (1), including a phone and / or a tablet and / or a computer and / or a television and / or a portable device, etc., for medical personnel to access the system and access the result data.
The invention includes network (2) to provide data exchange between numerous mobile terminals (1) and database (3).
The invention includes a network (2) to provide data exchange between numerous mobile terminals (1) and the prediction module (4.2) in the artificial intelligence module (4).
The network (2) in the invention includes various connection types such as wired, wireless communication connections or fiber optic cables.
Continuously updated and developed data regarding patients and expert opinions are transferred from the unlimited mobile terminal (1) to the database (3) in the invention over the network (2). The artificial intelligence module (4) in the invention includes a training module (4.1) and a prediction module (4.2).
Historical data is continuously retrieved from the unlimited mobile terminal (1) to the artificial intelligence module (4) included in the invention, from the database (3), which is equipped with continuously updated and developed data regarding patients and expert opinions.
In the invention, the data transferred from the database (3) to the artificial intelligence module (4) are transferred to the training module (4.1) in order to create the prediction models with the highest accuracy. In the training module (4.1), prediction models with the highest accuracy are created by processing data using different artificial intelligence algorithms.
In the invention, each new data coming from the database (3) unlimited mobile terminal (1) is continuously transferred to a dynamic training module (4.1). Each new data transferred to the training module (4.1) is continuously trained to create a model with high precision and accuracy.
In the invention, estimation is performed with the current estimation model created by using different artificial intelligence algorithms in the prediction module (4.2), which works synchronized with the training module (4.1).
In the invention, the result data of the disease and risk status obtained with the prediction model with the highest accuracy rate created in the prediction module (4.2) are transferred from the prediction module (4.2) to the relevant mobile terminal (1) for the health personnel to view.

Claims

CLAIMS - The invention relates to a health status analysis system over historical data containing mobile terminal (1), network (2) and database (3), and its feature is; artificial intelligence module (4), in which historical data is continuously transferred from the unlimited mobile terminal (1) from the database (3) equipped with continuously updated and developed data on patients and expert opinions,
- the training module (4.1), which operates using artificial intelligence algorithms, as a result of transferring data such as patient analysis and previous diseases from the central hospital system to the artificial intelligence module (4) in order to create the most accurate prediction model, it includes a prediction module (4.2) that works in sync with the training module (4.1) and has an up-to-date prediction model created using artificial intelligence algorithms. - As mentioned in Claim 1, it is a health status analysis system based on historical data, and its feature is; the database (3) is characterized by a dynamic training module (4.1) in which each new data coming from the unlimited mobile terminal (1) is continuously transferred. - As mentioned in Claim 1 or Claim 2, it is a health status analysis system based on appropriate historical data, and its feature is; it is characterized by the fact that it contains a training module (4.1) that ensures that each new data transferred is constantly trained in order to create a model with high sensitivity and accuracy. - As mentioned in Claim 1 or Claim 2, it is a health status analysis system based on appropriate historical data, and its feature is; it is characterized by the fact that it contains the prediction module (4.2), which enables the result data of the disease and risk status to be obtained with the prediction model with the highest accuracy. - As mentioned in Claim 1 or Claim 2, it is a health status analysis system based on appropriate historical data, and its feature is; it is characterized by the fact that it contains a prediction module (4.2) that allows the outcome data of the disease and risk status to be transferred to the relevant mobile terminal (1) for the viewing of healthcare personnel.
PCT/TR2022/051022 2022-07-28 2022-09-20 Health status analysis system on historical data WO2024025489A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
TR2022/011992 2022-07-28
TR2022/011992A TR2022011992A2 (en) 2022-07-28 2022-07-28 HEALTH STATUS ANALYSIS SYSTEM ON HISTORY DATA

Publications (1)

Publication Number Publication Date
WO2024025489A1 true WO2024025489A1 (en) 2024-02-01

Family

ID=84101252

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/TR2022/051022 WO2024025489A1 (en) 2022-07-28 2022-09-20 Health status analysis system on historical data

Country Status (2)

Country Link
TR (1) TR2022011992A2 (en)
WO (1) WO2024025489A1 (en)

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200303075A1 (en) * 2019-03-18 2020-09-24 Kundan Krishna System and a method to predict occurrence of a chronic diseases
CN113270197A (en) * 2021-06-03 2021-08-17 苏州立威新谱生物科技有限公司 Health prediction method, system and storage medium based on artificial intelligence
US20210272696A1 (en) * 2020-03-02 2021-09-02 University Of Cincinnati System, method computer program product and apparatus for dynamic predictive monitoring in the critical health assessment and outcomes study (chaos)
CN113421646A (en) * 2021-06-30 2021-09-21 平安科技（深圳）有限公司 Method and device for predicting duration of illness, computer equipment and storage medium
CN113470818A (en) * 2021-07-08 2021-10-01 建信金融科技有限责任公司 Disease prediction method, device, system, electronic device and computer readable medium
US20220076841A1 (en) * 2020-09-09 2022-03-10 X-Act Science, Inc. Predictive risk assessment in patient and health modeling
CN114188015A (en) * 2021-10-26 2022-03-15 北京清华长庚医院 Cerebral apoplexy disease prediction method and device based on artificial intelligence
US20220230759A1 (en) * 2020-09-09 2022-07-21 X- Act Science, Inc. Predictive risk assessment in patient and health modeling

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200303075A1 (en) * 2019-03-18 2020-09-24 Kundan Krishna System and a method to predict occurrence of a chronic diseases
US20210272696A1 (en) * 2020-03-02 2021-09-02 University Of Cincinnati System, method computer program product and apparatus for dynamic predictive monitoring in the critical health assessment and outcomes study (chaos)
US20220076841A1 (en) * 2020-09-09 2022-03-10 X-Act Science, Inc. Predictive risk assessment in patient and health modeling
US20220230759A1 (en) * 2020-09-09 2022-07-21 X- Act Science, Inc. Predictive risk assessment in patient and health modeling
CN113270197A (en) * 2021-06-03 2021-08-17 苏州立威新谱生物科技有限公司 Health prediction method, system and storage medium based on artificial intelligence
CN113421646A (en) * 2021-06-30 2021-09-21 平安科技（深圳）有限公司 Method and device for predicting duration of illness, computer equipment and storage medium
CN113470818A (en) * 2021-07-08 2021-10-01 建信金融科技有限责任公司 Disease prediction method, device, system, electronic device and computer readable medium
CN114188015A (en) * 2021-10-26 2022-03-15 北京清华长庚医院 Cerebral apoplexy disease prediction method and device based on artificial intelligence

Also Published As

Publication number Publication date
TR2022011992A2 (en) 2022-08-22

Similar Documents

Publication Publication Date Title
Bai et al. Chinese experts’ consensus on the Internet of Things-aided diagnosis and treatment of coronavirus disease 2019 (COVID-19)
Bervell et al. A comparative review of mobile health and electronic health utilization in sub-Saharan African countries
EP3255573A1 (en) Clinical decision supporting ensemble system and clinical decison supporting method using the same
US20190122770A1 (en) Lightweight Clinical Pregnancy Preterm Birth Predictive System and Method
KR20170140757A (en) A clinical decision support ensemble system and the clinical decision support method by using the same
CN103605911A (en) Intelligent community health care system control method based on Internet of things
US11200967B1 (en) Medical patient synergistic treatment application
CN108028074A (en) Patient coordinate's system and method
CN109102880A (en) Health monitor method and its device, system and computer readable storage medium
Onashoga et al. A mobile phone-based antenatal care support system
CN113053514A (en) Integrated system of wisdom city doctor based on 5G communication technology
Radhakrishnan et al. Investigating discrete event simulation method to assess the effectiveness of wearable health monitoring devices
CA3175840A1 (en) System and methods utilizing artificial intelligence algorithms to analyze wearable activity tracker data
CN112735579A (en) Rapid registration treatment system for emergency patients
WO2024025489A1 (en) Health status analysis system on historical data
Antonius et al. The internet of things (IoT) design for cardiac remote patient monitoring using business process re-engineering
Parikh et al. An update on growth and development of telemedicine with pharmacological implications
Lebedev et al. Systematization of the principles and methods of applying for digital medicine in oncology
Kapoor et al. The impact of insurance coverage during insurance reform on diagnostic resolution of cancer screening abnormalities
US11600366B2 (en) System and method for facilitating configuration modifications for a patient interface computer system based on risk of readmission of a patient
Kumar et al. Healthcare engineering using AI and distributed technologies
von Wangenheim et al. Direct impact on costs of the teledermatology-centered patient triage in the state of Santa Catarina
Bhatia et al. Deep Data Analytics: Future of Telehealth
Dewangan et al. Smart Healthcare and Intelligent Medical Systems
AU2021101675A4 (en) Consistent data-driven decision-making system for tele medicine applications using multitudinal and multimodal data

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 22953294

Country of ref document: EP

Kind code of ref document: A1