[go: up one dir, main page]

WO2018153029A1 - Système et procédé de notation et de recommandation de médecin basées sur une association de données - Google Patents

Système et procédé de notation et de recommandation de médecin basées sur une association de données Download PDF

Info

Publication number
WO2018153029A1
WO2018153029A1 PCT/CN2017/096126 CN2017096126W WO2018153029A1 WO 2018153029 A1 WO2018153029 A1 WO 2018153029A1 CN 2017096126 W CN2017096126 W CN 2017096126W WO 2018153029 A1 WO2018153029 A1 WO 2018153029A1
Authority
WO
WIPO (PCT)
Prior art keywords
doctor
node
hospital
information
disease
Prior art date
Legal status (The legal status 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 status listed.)
Ceased
Application number
PCT/CN2017/096126
Other languages
English (en)
Chinese (zh)
Inventor
张贯京
葛新科
王海荣
高伟明
张红治
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Qianhai AnyCheck Information Technology Co Ltd
Original Assignee
Shenzhen Qianhai AnyCheck Information Technology Co Ltd
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 Shenzhen Qianhai AnyCheck Information Technology Co Ltd filed Critical Shenzhen Qianhai AnyCheck Information Technology Co Ltd
Publication of WO2018153029A1 publication Critical patent/WO2018153029A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • 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
    • G16H40/20—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 management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms

Definitions

  • the present invention relates to the field of medical big data, and in particular, to a doctor rating recommendation system and method based on data association.
  • Big data technology can accelerate medical conjecture and discover the transformation of medical practice: With the growing private and public medical data, big data technology helps people store and manage medical big data and from large volume, high complexity The value of the data will be extracted, and related medical technologies and products will continue to emerge, which will likely open up a new golden generation for the medical industry.
  • the current medical data analysis system analyzes and processes medical big data, and does not consider the factors that the user evaluates to the doctor, nor does it refer to the medical big data based on the doctor evaluation information in the registration system.
  • doctors cannot be rated by big data, and patients often have to find the corresponding doctor through a large number of inquiries.
  • a primary object of the present invention is to provide a doctor rating evaluation system and method based on data association, which aims to solve the technical problem of not analyzing and processing and recommending a doctor based on the evaluation system in the process of medical big data processing.
  • the present invention provides a doctor rating evaluation system based on data association, which operates In the data center, the data center is connected to the hospital information system, the client, and the registered website through a network, and the doctor-ranking recommendation system based on the data association includes:
  • an obtaining module configured to obtain medical data from a hospital information system of each hospital
  • a creating module configured to parse medical data of each hospital, and create a list of disease types according to a disease type keyword
  • an obtaining module configured to obtain evaluation information from a registered website
  • an association module configured to perform a search in the evaluation information according to a node keyword in a disease type list, and associate the retrieved evaluation information with a node corresponding to the node keyword;
  • a rating module configured to score each doctor in the disease type list according to the retrieved evaluation information
  • the display module is configured to: when the user queries the corresponding disease through the client, recommend the doctor with the highest score to the user, and display it on the client of the user.
  • the medical data further includes a hospital name, a patient name, a patient's age, a diseased day, a disease cause, a disease diagnosis information, a drug name, a drug quantity, a doctor name, a doctor's office, a fee, and a patient's Contact information.
  • the disease type list is divided into three layers of nodes, the first layer node is a disease name node, the second layer node is a department node of the hospital where the disease type is located, and the third layer node is a doctor information node.
  • the evaluation information includes evaluation content, praise or bad review.
  • the present invention further provides a doctor rating recommendation method based on data association, which is applied to a data center, and the data center is connected to a hospital information system, a client, and a registered website through a network, and the method includes:
  • the highest rated doctor is recommended to the user and displayed on the user's client.
  • the medical data further includes a hospital name, a patient name, a patient's age, a diseased day, a disease cause, a disease diagnosis information, a drug name, a drug quantity, a doctor name, a doctor's office, a fee, and a patient's Contact information.
  • the disease type list is divided into three layers of nodes, the first layer node is a disease name node, the second layer node is a department node of the hospital where the disease type is located, and the third layer node is a doctor information node.
  • the step of associating the node information in the disease type list with the node information and associating the retrieved evaluation information with the node corresponding to the node keyword comprises the following steps: [0027] (1) Obtaining a node keyword in the disease type list, and searching for the corresponding evaluation information by using the keyword, wherein the node keyword in the disease type list may be a node name, or may be a certain one of the nodes Set the keyword;
  • an evaluation information includes a node keyword in the disease type list, the evaluation information is associated with a node corresponding to the node keyword.
  • a and b are fixed parameters.
  • the present invention adopts the above technical solution, and brings the technical effects as follows:
  • the medical data is analyzed by big data, thereby rating the doctor of the hospital, facilitating the patient.
  • the doctor who picks up the disease chooses the doctor, which saves the patient's inquiry.
  • FIG. 1 is a schematic diagram of an application environment of a doctor rating recommendation system based on data association according to the present invention
  • FIG. 2 is a schematic diagram of functional modules of a preferred embodiment of a physician association rating system based on data association of the present invention
  • FIG. 3 is a flow chart of a preferred embodiment of a doctor-ranking recommendation method based on data association of the present invention
  • FIG. 4 is a schematic diagram of a list of disease types of the present invention.
  • FIG. 1 is a schematic diagram of an application environment of a doctor rating recommendation system based on data association according to the present invention.
  • the data association based physician rating recommendation system 20 of the present invention operates in the data center 2.
  • the data center 2 is communicatively coupled to one or more hospital information systems 1 (illustrated by three in FIG. 1) via the network 3 to acquire a plurality of medical data from the hospital information system 1.
  • the medical data includes, but is not limited to, the name of the hospital, the name of the patient, the age of the patient, the disease, the cause of the disease, the diagnosis information of the disease, the name of the drug, the number of drugs, the name of the doctor, the department of the visit, the cost, and the contact information of the patient. (for example, email address, mobile number, and instant messaging account, etc.).
  • the network 3 may be a wired communication network or a wireless communication network.
  • the network 3 is preferably a wireless communication network including, but not limited to, a GSM network, a GPRS network, a CDMA network, a TD-SCDMA network, a WiMAX network, a TD-LTE network, an FDD-LTE network, and the like.
  • the data center 2 is communicably connected to one or more clients 4 (illustrated by taking three as an example in FIG. 1) through the network 3, and the doctor with the highest rating after the user is retrieved is recommended to the patient.
  • the data center 2 may further analyze and process the medical data, and send the analyzed disease association list (as shown in FIG. 4 to the associated list of diseases "fever") to the patient via the network 3.
  • Corresponding client 4 It should be noted that the client 4 is held by a user, and the user can obtain the client through the client 4. Medical data.
  • the data center 2 is communicatively connected to the website 5 through the network 3, and is used to obtain evaluation information of the patient from the website 5 from the website.
  • the registered website 5 provides an API interface, and the device or system accessing the API interface can obtain evaluation information from the registered website 5.
  • the data center 2 obtains the evaluation information of the doctor on the basis of the authorization of the registered website 5 (i.e., authorized access to the API interface provided by the registered website 5).
  • the registered website 5 is connected to the one or more hospital information systems 1, and the patient can register through the registered website 5, and then the registration information is sent to the hospital information system 1 to form the registration information of the hospital.
  • the user selects the hospital A internal medicine registration number on the registered website 5, and after the website 5 generates the registration information, the hospital information system 1 sent to the hospital A forms the registration information of the hospital A.
  • the visiting doctor can be evaluated on the registered website 5, and the registered website 5 retains the rating information for other patients to view.
  • the data center 2 is a server of a cloud platform or a data center, and can better manage and/or assist with the data transmission capability and data storage capability of the cloud platform or the data center.
  • the data center 2 is connected to the client 4.
  • the client 4 may be, but is not limited to, any other suitable portable electronic device such as a smart phone, a tablet computer, a personal digital assistant (PDA), a personal computer, an electronic signboard, and the like.
  • a smart phone such as a smart phone, a tablet computer, a personal digital assistant (PDA), a personal computer, an electronic signboard, and the like.
  • PDA personal digital assistant
  • FIG. 2 it is a schematic diagram of a functional module of a preferred embodiment of a physician-ranking recommendation system based on data association of the present invention.
  • the data association based doctor rating recommendation system 20 is applied to the data center 2.
  • the data center 2 includes, but is not limited to, a doctor association rating system 20 based on data association, a storage unit 22, a processing unit 24, and a communication unit 26.
  • the storage unit 22 may be a read only storage unit ROM, an electrically erasable storage unit EEPRO M, a flash storage unit FLASH or a solid hard disk.
  • the processing unit 24 may be a central processing unit (CPU), a microcontroller (MCU), a data processing chip, or an information processing unit having a data processing function.
  • CPU central processing unit
  • MCU microcontroller
  • data processing chip or an information processing unit having a data processing function.
  • the communication unit 26 is a wireless communication interface with remote wireless communication functions, for example, supports communication technologies such as GSM, GPRS, WCDMA, CDMA, TD-SCDMA, WiMAX, TD-LTE, FDD-LT E Communication interface.
  • the data association-based doctor rating recommendation system 20 includes, but is not limited to, an acquisition module 200, a creation module 210, an association module 220, a rating module 230, and a display module 240, and the module referred to in the present invention refers to a module.
  • a series of computer program instructions that can be executed by the processing unit 24 of the data center 2 and that are capable of performing a fixed function are stored in the storage unit 22 of the data center 2.
  • the acquisition module 200 is configured to acquire medical data from the hospital information system 1 of each hospital.
  • the hospital information system 1 provides a data import interface (eg, an application program interface, API), and a device or system that accesses the data import interface can be from the hospital information system.
  • a data import interface eg, an application program interface, API
  • the obtaining module 200 invokes an API interface provided by the hospital information system 1 to obtain medical data.
  • the medical data belongs to private information
  • the medical data is sent to the data center 2, and the encryption and decryption algorithm is adopted (for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm).
  • DES encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm.
  • DSA encryption and decryption algorithm for example, the MD5 encryption and decryption algorithm and the RSA encryption and decryption algorithm
  • AES encryption and decryption algorithm etc.
  • the creating module 210 is configured to parse the medical data of each hospital, and create a disease type list according to the disease type keyword.
  • the disease type list is divided into three layers of nodes, the first layer node is a disease name node (the node holds disease name information), and the second layer node is a department node of the hospital where the disease type is located (the node holds the name of the hospital department), The third layer node is the doctor information node (this node saves the doctor's name, job title, receiving volume, favorable rate, etc.).
  • the list of disease types is a list of disease "fever". In other embodiments, the list of disease types may be more than three layers (eg, four layers, five layers, or more)
  • the obtaining module 200 is configured to obtain evaluation information from the website 5 for registration.
  • the rating information may be, but is not limited to, rating content, praise or bad reviews, and the like.
  • the association module 220 is configured to perform a search in the evaluation information according to a node keyword in the disease type list, and associate the retrieved evaluation information with a node corresponding to the node keyword.
  • step of associating the retrieved evaluation information with the node corresponding to the node keyword according to the node keyword in the disease type list includes the following steps:
  • the node keyword in the disease type list may be a node name, or may be A preset keyword in the node.
  • the housekeeping word of the hospital department node is "XX X People's Hospital Internal Medicine YY doctor";
  • an evaluation information includes a node keyword in the disease type list, the evaluation information is associated with a node corresponding to the node keyword.
  • the rating module 230 is configured to score each doctor in the disease type list according to the retrieved evaluation information.
  • the display module 240 is configured to recommend the highest rated doctor to the patient when the user queries the corresponding disease through the client 4, and displays it on the client 4 of the user. Specifically, as shown in FIG. 4, if the doctor's score in the hospital of A hospital is up to 145 points, when the user queries the fever through the client 4, the doctor's information of the hospital A is displayed to the user. Client 4 on it.
  • FIG. 3 there is shown a flow chart of a preferred embodiment of the doctor-ranking recommendation method based on data association of the present invention.
  • the data association based doctor rating recommendation method is applied to the data center 2, and the method includes the following steps:
  • Step S10 The obtaining module 200 acquires medical data from the hospital information system 1 of each hospital.
  • the hospital information system 1 provides a data import interface (eg, an application program interface, an API), and a device or system that accesses the data import interface can be from the hospital information system.
  • a data import interface eg, an application program interface, an API
  • the obtaining module 200 invokes an API interface provided by the hospital information system 1 to obtain medical data.
  • the medical data belongs to private information
  • the medical data is sent to the data center 2
  • the encryption and decryption algorithm is adopted (for example, the MD5 encryption and decryption algorithm, RSA)
  • the encryption and decryption algorithm, the DES encryption and decryption algorithm, the DSA encryption and decryption algorithm, the AES encryption and decryption algorithm, etc.) first encrypt the medical data, and then transmit it to the data center 2.
  • Step S11 The creating module 210 parses the medical data of each hospital, and creates a disease type list according to the disease type keyword.
  • the disease type list is divided into three layers of nodes, the first layer node is the disease name node (the node holds the disease name), the second layer is the department node of the hospital where the disease type is located (the node holds the disease name), and the third layer For the doctor information node (this node saves the doctor's name, title, etc.).
  • the list of disease types is a list of diseases "fever”. In other embodiments, the list of disease types may be more than three layers (e.g., four layers, five layers, or more).
  • Step S12 The obtaining module 200 acquires the evaluation information from the registered website 5.
  • the rating information may be
  • Step S13 The association module 220 searches the evaluation information according to the node keyword in the disease type list, and associates the retrieved evaluation information with the node corresponding to the node keyword.
  • step of associating the retrieved evaluation information with the node corresponding to the node keyword according to the node keyword in the disease type list includes the following steps:
  • the node keyword in the disease type list may be a node name, or may be a node A default keyword.
  • the housekeeping word for the hospital department node is "XX"
  • the evaluation information is associated with a node corresponding to the node keyword.
  • Step S14 The rating module 230 scores each doctor in the disease type list according to the retrieved evaluation information.
  • Step S15 When the user queries the corresponding disease through the client 4, the display module 240 recommends the doctor with the highest score to the user and displays it on the client 4 of the patient. Specifically, as shown in Figure 4, if the doctor's score in the hospital of A hospital is up to 145 points, then when the patient queries the fever through the client 4, the doctor's information of the hospital A is displayed. Client 4 on it.
  • the present invention adopts the above technical solution, and brings the technical effects as follows: According to the data association-based doctor rating recommendation system and method of the present invention, big data analysis is performed on the medical data, thereby rating the doctor in the hospital, facilitating the patient. The doctor who picks up the disease chooses the doctor, which saves the patient's inquiry.

Landscapes

  • Business, Economics & Management (AREA)
  • Health & Medical Sciences (AREA)
  • General Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Primary Health Care (AREA)
  • Tourism & Hospitality (AREA)
  • General Health & Medical Sciences (AREA)
  • Child & Adolescent Psychology (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Epidemiology (AREA)
  • Biomedical Technology (AREA)
  • Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

L'invention concerne un système et un procédé de notation et de recommandation de médecin basées sur une association de données, ledit procédé comprenant : obtenir des données médicales à partir d'un système d'informations d'hôpital (1) de chaque hôpital (S10); analyser les données médicales de chaque hôpital, et créer une liste de types de maladie en fonction d'un mot-clé de type de maladie (S11); obtenir des informations d'avis public à partir d'un site Web d'avis d'enregistrement (S12); effectuer une recherche dans ledit site Web d'avis d'enregistrement en fonction d'un mot-clé de nœud dans la liste de types de maladie, et associer les informations d'avis extraites au nœud correspondant au mot-clé de nœud (S13); en fonction des informations d'avis extraites, noter chaque médecin dans la liste de types de maladie (S14); lorsqu'un utilisateur se renseigne sur une maladie correspondante au moyen d'un client (4), recommander le médecin ayant la note la plus élevée à l'utilisateur et l'afficher sur le client (4) de l'utilisateur (S15). Une analyse de données volumineuses est effectuée sur les données médicales de telle sorte qu'il est pratique pour un patient de trouver un médecin lorsqu'il souffre d'une maladie correspondante, ce qui permet d'économiser du temps lorsque le patient effectue une recherche.
PCT/CN2017/096126 2017-02-25 2017-08-05 Système et procédé de notation et de recommandation de médecin basées sur une association de données Ceased WO2018153029A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710105145.1A CN106780234A (zh) 2017-02-25 2017-02-25 基于数据关联的医生评级推荐系统及方法
CN201710105145.1 2017-02-25

Publications (1)

Publication Number Publication Date
WO2018153029A1 true WO2018153029A1 (fr) 2018-08-30

Family

ID=58959480

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/096126 Ceased WO2018153029A1 (fr) 2017-02-25 2017-08-05 Système et procédé de notation et de recommandation de médecin basées sur une association de données

Country Status (2)

Country Link
CN (1) CN106780234A (fr)
WO (1) WO2018153029A1 (fr)

Families Citing this family (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106780234A (zh) * 2017-02-25 2017-05-31 深圳市前海安测信息技术有限公司 基于数据关联的医生评级推荐系统及方法
CN107545368A (zh) * 2017-08-31 2018-01-05 江西博瑞彤芸科技有限公司 关联信息的匹配方法
CN108039198A (zh) * 2017-12-11 2018-05-15 重庆邮电大学 一种面向移动医疗的医生推荐方法及系统
CN108122607A (zh) * 2018-01-12 2018-06-05 重庆至道医院管理股份有限公司 基于大数据进行患者体验评测优化服务系统
CN108831522A (zh) * 2018-05-28 2018-11-16 陈丽璇 一种自动编码的医保病种分值付费系统及其构建方法
EP3818545B1 (fr) * 2018-07-02 2024-08-28 Baxter International Inc. Base de données de graphiques pour suivi et gestion d'épidémies
CN109409709A (zh) * 2018-10-12 2019-03-01 宜昌市中心人民医院 智能职称评定系统
CN109949909A (zh) * 2018-10-16 2019-06-28 陕西医链区块链集团有限公司 一种基于区块链的医疗健康系统
WO2020080504A1 (fr) * 2018-10-19 2020-04-23 ソニー株式会社 Système de traitement d'informations médicales, dispositif de traitement d'informations médicales et procédé de traitement d'informations médicales
CN110277155A (zh) * 2019-06-19 2019-09-24 秒针信息技术有限公司 导诊方法及装置、存储介质、电子装置
CN110491490A (zh) * 2019-07-11 2019-11-22 深圳市翩翩科技有限公司 一种医生评估方法及装置
CN110931113A (zh) * 2019-10-09 2020-03-27 北京全域医疗技术集团有限公司 一种基于互联网云平台的医院管理运营系统和方法
CN111143668A (zh) * 2019-12-06 2020-05-12 广州市医康传媒信息技术有限公司 一种医疗资源推荐信息处理系统、方法、装置及存储介质
CN111370100A (zh) * 2020-03-11 2020-07-03 深圳小佳科技有限公司 基于云端服务器的整容推荐方法及系统
JP7525319B2 (ja) * 2020-07-17 2024-07-30 富士フイルムヘルスケア株式会社 医療データ評価活用システム、および、医療データ評価活用方法
CN112086154A (zh) * 2020-09-11 2020-12-15 河南省儿童医院郑州儿童医院 儿科信息智能建档方法、装置、设备及存储介质
CN112509656A (zh) * 2020-12-16 2021-03-16 平安国际智慧城市科技股份有限公司 基于医疗机构的等级评价方法、装置、计算机设备及介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103093315A (zh) * 2013-01-18 2013-05-08 余飞 基于多元评价主体的医德档案量化评价系统
US20140129260A1 (en) * 2011-07-14 2014-05-08 Korea University Research And Business Foundation Method and device for providing application service using health classification information
CN106202945A (zh) * 2016-07-13 2016-12-07 张志华 一种高安全性的医患信息管理系统
CN106227880A (zh) * 2016-08-01 2016-12-14 挂号网（杭州）科技有限公司 医生搜索推荐的实现方法
CN106780234A (zh) * 2017-02-25 2017-05-31 深圳市前海安测信息技术有限公司 基于数据关联的医生评级推荐系统及方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140129260A1 (en) * 2011-07-14 2014-05-08 Korea University Research And Business Foundation Method and device for providing application service using health classification information
CN103093315A (zh) * 2013-01-18 2013-05-08 余飞 基于多元评价主体的医德档案量化评价系统
CN106202945A (zh) * 2016-07-13 2016-12-07 张志华 一种高安全性的医患信息管理系统
CN106227880A (zh) * 2016-08-01 2016-12-14 挂号网（杭州）科技有限公司 医生搜索推荐的实现方法
CN106780234A (zh) * 2017-02-25 2017-05-31 深圳市前海安测信息技术有限公司 基于数据关联的医生评级推荐系统及方法

Also Published As

Publication number Publication date
CN106780234A (zh) 2017-05-31

Similar Documents

Publication Publication Date Title
WO2018153029A1 (fr) Système et procédé de notation et de recommandation de médecin basées sur une association de données
WO2018153030A1 (fr) Système et procédé de notation et de recommandation de médecin basées sur une page web à des fins d'informatisation médicale
US10636515B2 (en) Medical or health information search support apparatus and medical or health information search support system
US11562812B2 (en) Computer implemented method for secure management of data generated in an EHR during an episode of care and a system therefor
CN103617267B (zh) 社交化扩展搜索方法及装置、系统
WO2018082261A1 (fr) Interrogation médicale informatisée de données médicales et système et procédé d'audit basés sur un dossier médical électronique
Teng et al. Scientific approaches to AIDS prevention and control in China
WO2017152638A1 (fr) Système et procédé d'analyse et de traitement de mégadonnées médicales basés sur une consultation de page web
JP2011513811A5 (fr)
Peitzmeier et al. Acceptability of microbicidal vaginal rings and oral pre-exposure prophylaxis for HIV prevention among female sex workers in a high-prevalence US city
WO2018082263A1 (fr) Procédé et système d'analyse de dossiers médicaux électroniques par mise en correspondance de mots-clés pour l'informatisation médicale
WO2019095551A1 (fr) Système de soins de santé régional et procédé de partage, d'intégration et de recherche d'enregistrements médicaux électroniques
WO2018082262A1 (fr) Système et procédé informatisés de recherche d'informations médicales pour dossier médical électronique basé sur la reconnaissance de l'iris
WO2017148170A1 (fr) Système et procédé d'analyse de données médicales volumineuses et d'alerte précoce
WO2018165968A1 (fr) Système et procédé d'évaluation et de recommandation de commerçant basées sur une recherche de pages web
WO2018082259A1 (fr) Système et procédé d'interrogation de données médicales de dossier médical électronique appliqué à un terminal mobile
Liu et al. Scabies knowledge among undergraduate nursing students in China: A questionnaire survey
CN111052259A (zh) 使用医疗术语表达的设备上搜索
Pandey et al. Clinical Trials Registry-India: Redefining the conduct of clinical trials
Sneha et al. E-Health: Value proposition and technologies enabling collaborative Healthcare
CN102360390A (zh) 一种基于医学关键词的知识云数据库检索方法和系统
WO2018082260A1 (fr) Système et procédé d'interrogation d'informations de dossier médical électronique sur la base d'une base de données partitionnée
CN110929292B (zh) 一种医疗数据的搜索方法及装置
CN107609017A (zh) 通过自定义热词实现医疗行业智能搜索咨询的方法及系统
Desai et al. Characterizing services advertised on crisis pregnancy center websites

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: 17897263

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 02/01/2020)

122 Ep: pct application non-entry in european phase

Ref document number: 17897263

Country of ref document: EP

Kind code of ref document: A1