How Artificial Intelligence Can Help the Prediction of Treatment Outcomes of Tuberculosis: A Systematic Literature Review

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dc.contributor.authorLino Ferreira Da Silva Barros, Maicon Herverton
dc.contributor.authorDa Silva Neto, SebastiĆ£o Rogerio
dc.contributor.authorAlmeida Rodrigues, Maria Gabriela
dc.contributor.authorDe Souza Sampaio, Vanderson
dc.contributor.authorEndo, Patricia Takako
dc.date.accessioned2022-12-27T18:58:38Z
dc.date.available2022-12-27T18:58:38Z
dc.date.issued2023-01-03
dc.description.abstractTuberculosis (TB) is a disease with a global impact that over the years has mainly affected the poorest countries. After confirming the TB diagnosis, the health professional needs to analyze the severity of the clinical situation of the patient in order to make decisions about their treatment, which may include admission to Intensive Care Unit (ICU). The aim of this paper is to present a systematic review focused on Machine Learning (ML) models for predicting TB treatment outcomes. From 253 articles found through a boolean search, only 12 of them were classified as relevant, presented and discussed in this work. Results show that the current literature is focused on binary classification, mainly using tree-based ML algorithms. Based on the results of this systematic review, we state that there are many opportunities to develop new scientific projects in this area, highlighting the need for rigorous methodology to conduct models' configuration as well as experiments to evaluate them.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2023.173
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.other2b5f4d38-86a4-4489-8632-92a731bb778d
dc.identifier.urihttps://hdl.handle.net/10125/102803
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectService Analytics
dc.subjectartificial intelligence
dc.subjectprediction
dc.subjectprognosis
dc.subjecttreatment outcomes
dc.subjecttuberculosis
dc.titleHow Artificial Intelligence Can Help the Prediction of Treatment Outcomes of Tuberculosis: A Systematic Literature Review
dc.type.dcmitext
prism.startingpage1386

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