Application of Artificial Intelligence in Healthcare

Bibliographic Details
Main Author: Tavares, Jorge
Publication Date: 2024
Format: Other
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/166260
Summary: Tavares, J. (2024). Application of Artificial Intelligence in Healthcare: The Need for More Interpretable Artificial Intelligence. Acta Medica Portuguesa, 37(6), 411-414. https://doi.org/10.20344/amp.20469
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spelling Application of Artificial Intelligence in HealthcareThe Need for More Interpretable Artificial IntelligenceArtificial IntelligenceDelivery of Health CareMachine LearningAprendizagem AutomáticaInteligência ArtificialPrestação de Cuidados de SaúdeMedicine(all)Tavares, J. (2024). Application of Artificial Intelligence in Healthcare: The Need for More Interpretable Artificial Intelligence. Acta Medica Portuguesa, 37(6), 411-414. https://doi.org/10.20344/amp.20469Understanding artificial intelligence (AI) and its different types is of the utmost importance for the application of this technology in healthcare. Artificial intelligence is a field of knowledge which combines computer science and advanced statistics to support problem-solving. It is divided in two sub-fields: machine learning (ML) and deep learning. The ML concept resides in the ability of using computer algorithms that have the capability to recognize patterns and efficiently learn to train the model to predict, make recommendations or find data patterns. After a sufficient number of repetitions and algorithm adjustments, the machine becomes capable to accurately predict an output. Deep learning is a newer and more complex approach of AI that uses deep neural networks. The neural network starts with an input layer that then progresses to a variable number of hidden layers. Since the algorithm uses multiple layers with deep neural networks, it can successively refine itself, without explicitly programmed directions. It is a fact that, by using deep learning, the models usually achieve higher accuracy compared with ML. Still, when using ML, it is frequently possible to better understand which are the input variables that have more influence on the output variables. In both medical and clinical practices, it is often particularly relevant to understand why an AI technique is suggesting a certain classification or direction for a certain action. Not only in healthcare but also in other fields of knowledge, explain-able AI (also called XAI) is growing its influence. The current European legal regulation, specifically the General Data Protection Regulation (GDPR), requires that automated models provide meaningful information about the rationale on how the algorithm operates. The goal of this article is not to provide an exhaustive view about all existing AI models and explainable AI, but instead to provide a summarized and easy to understand view of what should be considered when implementing AI in healthcare and in clinical practice.Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNTavares, Jorge2024-04-16T00:30:38Z2024-06-032024-06-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/other5application/pdfhttp://hdl.handle.net/10362/166260eng1646-0758PURE: 88356715https://doi.org/10.20344/amp.20469info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-08T01:33:35Zoai:run.unl.pt:10362/166260Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:51:09.331477Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Application of Artificial Intelligence in Healthcare
The Need for More Interpretable Artificial Intelligence
title Application of Artificial Intelligence in Healthcare
spellingShingle Application of Artificial Intelligence in Healthcare
Tavares, Jorge
Artificial Intelligence
Delivery of Health Care
Machine Learning
Aprendizagem Automática
Inteligência Artificial
Prestação de Cuidados de Saúde
Medicine(all)
title_short Application of Artificial Intelligence in Healthcare
title_full Application of Artificial Intelligence in Healthcare
title_fullStr Application of Artificial Intelligence in Healthcare
title_full_unstemmed Application of Artificial Intelligence in Healthcare
title_sort Application of Artificial Intelligence in Healthcare
author Tavares, Jorge
author_facet Tavares, Jorge
author_role author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Tavares, Jorge
dc.subject.por.fl_str_mv Artificial Intelligence
Delivery of Health Care
Machine Learning
Aprendizagem Automática
Inteligência Artificial
Prestação de Cuidados de Saúde
Medicine(all)
topic Artificial Intelligence
Delivery of Health Care
Machine Learning
Aprendizagem Automática
Inteligência Artificial
Prestação de Cuidados de Saúde
Medicine(all)
description Tavares, J. (2024). Application of Artificial Intelligence in Healthcare: The Need for More Interpretable Artificial Intelligence. Acta Medica Portuguesa, 37(6), 411-414. https://doi.org/10.20344/amp.20469
publishDate 2024
dc.date.none.fl_str_mv 2024-04-16T00:30:38Z
2024-06-03
2024-06-03T00:00:00Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/166260
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1646-0758
PURE: 88356715
https://doi.org/10.20344/amp.20469
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dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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repository.mail.fl_str_mv info@rcaap.pt
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