Reliable digital physician assistant to identify high-risk patients
WEBIOMED is a Clinical Decision Support System (CDSS) that use machine learning and artificial intelligence
WEBIOMED is a Clinical Decision Support System (CDSS) that use machine learning and artificial intelligence
Ready-made, trained solution to identify high-risk patients, to prevent morbidity and mortality.
Automatic risk stratification of patients
A more efficient organization of preventive work aimed at personal group of patients with a high risk of complications and death
The ability to route patients depending on the assessment obtained
Reduced morbidity and mortalityReliable digital assistant, trained on the results of evidence-based medicine and modern clinical guidelines.
Automatic Identification of Risk Factors
Automatic determination of the likelihood of developing a disease
Compliance with clinical practice guidelines
Reduced time of the patient risk assessmentPowerful artificial intelligence to evaluate medical data and identify risk factors without development costs.
The addition of medical decision support functions
Ready service for evaluating EHR and to identify the risk factorsReducing the costs of development of medical information systemDuring working with electronic medical record (EHR) physicians use the special command to call CDSS. The de-identified electronic health records are send to CDSS Webiomed for assessment on this command.
WEBIOMED identifies risk factors and predict the likelihood or even death of a patient. It generates individual recommendations for the prevention of the diseases.
The answer sends to the information system that has requested the data analysis before. The user sees the result on EHRs workplace.
Artificial intelligence for cardiovascular risks assessment
Авторы:
Kuznetsova Tatyana
•
Gusev Aleksander
•
Igor Korsakov
Cardiovascular disease (CVD) is one of the leading causes of death and disability in most countries of the world, including Russia. According to Russian Federal State Statstics Service (Rosstat) in 2016, 904 thousand people died from diseases of the circulatory system in Russia, which amounted to 47.8% in the structure of the causes of mortality. A significant proportion of this morbidity and mortality could be prevented through early diagnosed and prevention strategies, both for people with established disease and for those at high risk of developing disease.
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The basic recommendations for the creation and development of information systems in health care based on artificial intelligence
Авторы:
Gusev Aleksander
•
Artificial intelligence is becoming one of the main drivers in solving serious problems of medicine and health, such as inadequate resources, further improving efficiency, quality and speed of work. All over the world, more and more solutions are being developed in this area. However, the more new products appear, the more questions and problems arise. The work analyzes some foreign publications and research results, which studied the main problems associated with the creation and implementation of artificial intelligence in health care. As a result of the analysis, a number of practical recommendations were formulated that will help increase the likelihood of successful creation and introduction of such products in the practical link of health.
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Artificial Intelligence in Medicine and Healthcare
Авторы:
Gusev Aleksander
•
The article discusses the prospects for using artificial intelligence technologies in medicine and healthcare. The history of artificial intelligence development is described. The technologies of machine learning and neural networks are analyzed. The review of already implemented artificial intelligence projects is provided. The forecast of the most promising directions of the artificial intelligence technologies development, according to the authors, for the near future is given.
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Prospects for neural networks and deep machine Learning in creating health solutions
Авторы:
Gusev Aleksander
The paper gives an overview of the prospects of using neural networks and deep machine learning in the creation of artificial intelligence systems for healthcare. The definition and explanations on the technologies of machine learning and neural networks are given. The review of already implemented artificial intelligence projects is presented, as well as the forecast of the most promising directions of development in the near future
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Clinical Decisions Support in medical information systems of a medical organization
Авторы:
Gusev Aleksander
•
In the article the review of various possibilities of support of acceptance of medical decisions in medical information systems of the medical organizations is presented. The description of functional requirements and prospects in terms of increasing the effectiveness of medical information systems in the informatization of clinical work of doctors
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12/08/2019 • Zdrav.fom
AI will help Yamal physicians to identify dangerous diseases at an early stages
09/04/2019 • Ministry of Health of Russian Federation
AI will help Yamal physicians to identify dangerous diseases at an early stages
06/05/2019 • National Technology Initiative (NTI)
How artificial intelligence can help physicians in their work
We decided to develop CDSS (clinical decision support system) in summer, 2018.
The idea of creating this system is to support, help physicians and health care organizers in making more effective decision for improving quality of patients care and mortality lessen
We have well -balanced team of the experts in medicine, machine learning and information technologies.
Our goal is to prevent the diseases
National Base of medical knowledge
The Association of Developers and Users of Artificial Intelligence Systems in Medicine
National Technology Initiative
The program for creation of fundamentally new markets and the creation of conditions for global technological leadership of Russia
Owners of high-quality structured electronic medical data are invited to join the affiliate program. We include your work in our product, in return, you use WEBIOMED for free in your work.
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