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Approaches to Medical Decision-Making Based on Big Clinical Data
The paper discusses different approaches to building a medical decision support system based on big data. The authors sought to abstain from any data reduction and apply universal teaching and big data processing methods independent of disease classification standards. The paper assesses and compare...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008823/ https://www.ncbi.nlm.nih.gov/pubmed/29973977 http://dx.doi.org/10.1155/2018/3917659 |
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author | Malykh, V. L. Rudetskiy, S. V. |
author_facet | Malykh, V. L. Rudetskiy, S. V. |
author_sort | Malykh, V. L. |
collection | PubMed |
description | The paper discusses different approaches to building a medical decision support system based on big data. The authors sought to abstain from any data reduction and apply universal teaching and big data processing methods independent of disease classification standards. The paper assesses and compares the accuracy of recommendations among three options: case-based reasoning, simple single-layer neural network, and probabilistic neural network. Further, the paper substantiates the assumption regarding the most efficient approach to solving the specified problem. |
format | Online Article Text |
id | pubmed-6008823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-60088232018-07-04 Approaches to Medical Decision-Making Based on Big Clinical Data Malykh, V. L. Rudetskiy, S. V. J Healthc Eng Research Article The paper discusses different approaches to building a medical decision support system based on big data. The authors sought to abstain from any data reduction and apply universal teaching and big data processing methods independent of disease classification standards. The paper assesses and compares the accuracy of recommendations among three options: case-based reasoning, simple single-layer neural network, and probabilistic neural network. Further, the paper substantiates the assumption regarding the most efficient approach to solving the specified problem. Hindawi 2018-06-04 /pmc/articles/PMC6008823/ /pubmed/29973977 http://dx.doi.org/10.1155/2018/3917659 Text en Copyright © 2018 V. L. Malykh and S. V. Rudetskiy. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Malykh, V. L. Rudetskiy, S. V. Approaches to Medical Decision-Making Based on Big Clinical Data |
title | Approaches to Medical Decision-Making Based on Big Clinical Data |
title_full | Approaches to Medical Decision-Making Based on Big Clinical Data |
title_fullStr | Approaches to Medical Decision-Making Based on Big Clinical Data |
title_full_unstemmed | Approaches to Medical Decision-Making Based on Big Clinical Data |
title_short | Approaches to Medical Decision-Making Based on Big Clinical Data |
title_sort | approaches to medical decision-making based on big clinical data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008823/ https://www.ncbi.nlm.nih.gov/pubmed/29973977 http://dx.doi.org/10.1155/2018/3917659 |
work_keys_str_mv | AT malykhvl approachestomedicaldecisionmakingbasedonbigclinicaldata AT rudetskiysv approachestomedicaldecisionmakingbasedonbigclinicaldata |