Open AccessDecision support technology for clinical data cognitive analysis
Author(s) -
N. V. Lavrinenko,
D. A. Gulyaev,
В. А. Мануковский
Publication year - 2022
Publication title -
nejrohirurgiâ
Language(s) - English
Resource type - Journals
eISSN - 2587-7569
pISSN - 1683-3295
DOI - 10.17650/1683-3295-2021-23-4-121-125
Subject(s) - surrender , modalities , identification (biology) , computer science , decision support system , cognition , risk analysis (engineering) , artificial neural network , big data , quality (philosophy) , information technology , data science , knowledge management , artificial intelligence , psychology , medicine , data mining , psychiatry , sociology , social science , philosophy , botany , epistemology , biology , operating system , archaeology , history
A practicing physician is faced with decision-making problems in uncertainty terms in his daily activities such as a lot of different information about the patient. Diagnostic issues, identification of patient management leading modalities is associated with the demand for high-quality prognosis of the disease course, calculating the risks of complications and adverse outcomes that especially problematic in emergency situations. The human brain is significantly surrender to modern computers in processing power, but it is able to instantly interpret information and analyze it, and also it is able to learn, form ideas, make conclusions. Attempt of association both the computational power and human brain intuitive analysis was reflected in the construction of computer programs based on the “Neural networks”. Together with the information technology development, the design of new neural networks configurations, and their training principles, its chances turn up in the physician daily activity decision making sphere.