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Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects
Artificial intelligence (AI)-aided decision support has developed rapidly to meet the needs for effective analysis of substantial data sets from electronic medical records and medical images generated daily, and computer-assisted intelligent drug design. In clinical practice, paediatricians make med...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493240/ https://www.ncbi.nlm.nih.gov/pubmed/32924683 http://dx.doi.org/10.1177/0300060520945141 |
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author | Li, Yawen Zhang, Tiannan Yang, Yushan Gao, Yuchen |
author_facet | Li, Yawen Zhang, Tiannan Yang, Yushan Gao, Yuchen |
author_sort | Li, Yawen |
collection | PubMed |
description | Artificial intelligence (AI)-aided decision support has developed rapidly to meet the needs for effective analysis of substantial data sets from electronic medical records and medical images generated daily, and computer-assisted intelligent drug design. In clinical practice, paediatricians make medical decisions after obtaining a large amount of information about symptoms, physical examinations, laboratory test indicators, special examinations and treatments. This information is used in combination with paediatricians’ knowledge and experience to form the basis of clinical decisions. This diagnosis and therapeutic strategy development based on large amounts of information storage can be applied to both large clinical databases and data for individual patients. To date, AI applications have been of great value in intelligent diagnosis and treatment, intelligent image recognition, research and development of intelligent drugs and intelligent health management. This review aims to summarize recent advances in the research and clinical use of AI in paediatrics. |
format | Online Article Text |
id | pubmed-7493240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-74932402020-09-23 Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects Li, Yawen Zhang, Tiannan Yang, Yushan Gao, Yuchen J Int Med Res Review Artificial intelligence (AI)-aided decision support has developed rapidly to meet the needs for effective analysis of substantial data sets from electronic medical records and medical images generated daily, and computer-assisted intelligent drug design. In clinical practice, paediatricians make medical decisions after obtaining a large amount of information about symptoms, physical examinations, laboratory test indicators, special examinations and treatments. This information is used in combination with paediatricians’ knowledge and experience to form the basis of clinical decisions. This diagnosis and therapeutic strategy development based on large amounts of information storage can be applied to both large clinical databases and data for individual patients. To date, AI applications have been of great value in intelligent diagnosis and treatment, intelligent image recognition, research and development of intelligent drugs and intelligent health management. This review aims to summarize recent advances in the research and clinical use of AI in paediatrics. SAGE Publications 2020-09-14 /pmc/articles/PMC7493240/ /pubmed/32924683 http://dx.doi.org/10.1177/0300060520945141 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Review Li, Yawen Zhang, Tiannan Yang, Yushan Gao, Yuchen Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title | Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title_full | Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title_fullStr | Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title_full_unstemmed | Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title_short | Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
title_sort | artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493240/ https://www.ncbi.nlm.nih.gov/pubmed/32924683 http://dx.doi.org/10.1177/0300060520945141 |
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