Artificial intelligence: Neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes

Chronic Diseases and Translational Medicine - Tập 2 - Trang 166-172 - 2016
Igor Vyacheslavovich Buzaev1,2, Vladimir Vyacheslavovich Plechev2, Irina Evgenievna Nikolaeva3, Rezida Maratovna Galimova2
1Interventional Cardiology 1 Department, GBUZ Republic Heart Centre, Ufa, Russia
2Bashkir State Medical University, Ufa, Russia
3GBUZ Republic Heart Centre, Ufa, Russia

Tóm tắt

AbstractObjectiveThe continuous uninterrupted feedback system is the essential part of any well‐organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision‐making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases.MethodaLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG) and percutaneous coronary intervention (PCI) in order to achieve a higher 5‐year survival rate in patients with angina based on the experience of 5107 patients.ResultsThe neural network was trained by 4679 patients who achieved 5‐year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient (r) of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5‐year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679) vs. 20.3% (87/428), P = 0.065)].ConclusionThe study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5‐year survival rate in patients with angina.

Tài liệu tham khảo

10.1093/ejcts/ezu366 10.1016/j.jcin.2011.01.008 10.1016/j.atherosclerosis.2012.09.011 Selivanov S.G., 2012, Sistemotechnica innovatsionnoy podgotovki proizvodstva v mashinostroenii Poole D., 1998, Computational Intelligence: A Logical Approach I.V.Buzaev E.V.M.Programma.Osteon Software Bol'nitsa. Registration Number 2004610140. Official nyj byulleten Programmy dlya EhVM Bazy dannyh Topologii integral'nyh mikroskhem.2004 I.E.Nikolaeva V.V.Plechev I.A.Nagaev et al.Programma EVM. On‐line sistema dispansernogo nabludeniya dlya respublicanskogo kardiologicheskogo dispansera. Registration Number 2013619040. Oficial'nyj byulleten' «Programmy dlya EhVM Bazy dannyh Topologii integral'nyh mikroskhem».2013 Fülöp J., 2005, Introduction to Decision Making Methods Keeney R.L., 1976, Decision with Multiple Objectives: Performances and Value Trade‐offs 10.1016/S0305-0483(97)00040-6 P.Csáki T.Rapcsák P.Turchányi M.Vermes.Research and Development for Group Decision Aid in Hungary by WINGDSS A Microsoft Windows Based Group Decision Support System Working Paper of the Laboratory of Operations Research and Decision Systems (LORDS) WP 93‐91993;19 10.1016/0167-9236(92)90003-8 10.1016/S0377-2217(03)00153-X 10.1016/S0377-2217(02)00273-4
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Chronic Diseases and Translational Medicine

Tập 2

166-172

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