information community file
Intelligent medical treatment
Based on the platform capability of Lingyi Zhihui technology, construct a series of products such as clinical auxiliary decision-making system, fundus image analysis system, medical big data overall solution, intelligent pre diagnosis assistant, chronic disease management platform, etc. to serve the whole scene inside and outside the hospital
Cooperation consulting
  • Typical business scenarios
  • Product advantages
  • Customer Stories
  • Related products and services
Typical business scenarios
  • Clinical assistant decision system
  • Medical big data governance
  • Fundus image analysis system
  • Intelligent pre diagnosis assistant
Application value
Improve diagnosis and treatment ability
Launch an auxiliary diagnostic system that meets the needs of grassroots doctors, and help them improve their full range of capabilities in consultation, diagnosis, medication, etc
Full coverage of rating requirements
Match all rating capability requirements, covering the detailed scenarios that cannot be covered by other manufacturers' products, such as inspection, care, hand anesthesia, etc
Programme composition
Through learning massive teaching materials, clinical guidelines, pharmacopoeia and high-quality medical records of Grade III A hospitals, and based on Baidu natural language processing, knowledge mapping and other AI technologies, we will build a clinical auxiliary decision-making system that follows evidence-based medicine to improve medical quality and reduce medical risks. The system includes multiple functions such as auxiliary inquiry, auxiliary diagnosis, treatment scheme recommendation, medical order quality control, etc
1. Auxiliary diagnosis: recommend the most relevant diseases, related symptoms and signs based on symptoms, diseases, and examination results, and infer the possibility of potential diseases from high to low according to the diagnosis results
2. Recommended treatment plan: recommend reasonable examination, medication and surgical treatment plans according to the patient's basic information, chief complaint, current medical history and other medical record information
3. Recommendation of similar medical records: based on real-time analysis of medical records, help clinicians learn from the characteristics of historical cases, diagnosis and treatment methods, and treatment effects, and learn from diagnosis and treatment ideas
4. Quality control of medical orders: comprehensively judge the rationality of patients' medication, inspection and inspection orders according to the patient's medical history, diagnosis, inspection results, historical medication and other information
5. Connotative quality control of medical records: provide connotative quality control services around the Inpatient Medical Record Quality Checklist and common problems of hospital medical records, improve link quality control ability, and improve the efficiency of final quality control
6. Medical knowledge query: if doctors want to further understand the recommended diseases, the system can provide a list of candidate knowledge through query keywords
7. Auxiliary inquiry: guide basic level doctors to inquire about the specific attributes of each symptom of the patient in detail, and the inquiry content can automatically generate the electronic medical record of the patient
Customer Stories
Product advantages
Leading evidence-based AI capability
Build a solid underlying technical foundation based on Baidu Brain 5.0 full line AI technology, and build an evidence-based AI technology framework that follows medical logic through deep integration with medical knowledge and medical experience
Authoritative medical knowledge
It has a team of dozens of full-time medical experts from top three hospitals; Reach deep strategic cooperation with authoritative medical knowledge publishers such as the People's Health Publishing House; Deep cooperation with experts and doctors from dozens of well-known hospitals, such as Zhongshan Eye Center of Sun Yat sen University, PLA General Hospital, Shengjing Hospital, Peking University International, etc
High level security
Based on the open-source in-depth learning platform independently developed by Baidu, the whole process is independently controllable, reliable and safe; Ensure the security and compliant use of medical data through a set of strictly audited data security solutions covering physical security, network security and business security
Customer Stories
Lingyi Zhihui has served nearly 1000 medical institutions, improved medical quality and service capacity, and helped to realize the national strategy of healthy China 2030
  • The First Affiliated Hospital of Nanchang University
    Lingyi Zhihui CDSS assisted hospitals successfully passed the electronic medical record rating and interconnection rating, improving medical safety and clinical application effect
    The First Affiliated Hospital of Nanchang University
    Lingyi Zhihui CDSS has deployed the functions of auxiliary diagnosis, treatment scheme recommendation, medical order quality control, rule maintenance platform, nursing decision support system and so on in the hospital to assist the hospital to successfully pass the electronic medical record rating, interconnection rating, further improve medical safety and clinical application effect
  • Pinggu District Primary Hospital
    Lingyi Zhihui CDSS has covered 18 medical institutions and 200 doctors in Pinggu, significantly improving the level of grass-roots diagnosis and treatment
    Pinggu District Primary Hospital
    Lingyi Zhihui CDSS launched six modules in Pinggu District, namely, auxiliary consultation, auxiliary diagnosis, treatment scheme recommendation, medical order quality control, similar medical record recommendation, and knowledge query. The system has operated for nearly half a year and has served 200 grassroots doctors in Pinggu District, improving the level of grassroots diagnosis and treatment
  • PLA General Hospital
    Lingyi Zhihui helps hospitals significantly improve data utilization efficiency. Through in-depth structuring of specialized diseases, the average data processing time of each patient can be saved by 30-40 minutes
    PLA General Hospital
    Taking the deep structure of special diseases as an example, the accuracy and recall rate of deep structured extraction of special disease medical records of gastric cancer, breast cancer, lung cancer and other special diseases reached more than 96%, and the average data processing time of each patient saved 30-40 minutes
  • Zhaoqing Primary Hospital
    As of September this year, Lingyi Zhihui's fundus image analysis capability has helped 1136 grassroots people in Zhaoqing and early detect eye disease risks such as Tangwang, glaucoma and macular lesions
    Zhaoqing Primary Hospital
    Lingyi Zhihui has implanted its fundus image analysis capability into more than ten basic hospitals in Zhaoqing, so that patients can obtain expert level fundus screening services without leaving the county. As of September this year, it has helped 1136 basic people and early detection of diabetic retinopathy, macular lesions, glaucoma and other eye diseases
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Technical capability
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Language and knowledge
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