Preliminary Results to Predict Tuberculosis Outcomes Applying Traditional and Automated Machine Learning Models-Reference-Cited by-同舟云学术

Preliminary Results to Predict Tuberculosis Outcomes Applying Traditional and Automated Machine Learning Models

Published:2023 Issue: Volume:219 Page:1365-1372
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Mioto Ana Clara de Andrade,Mozini Mariana Tavares,Segamarchi Renan Barbieri,Soares Giovane Thomazini,Martins Pedro Emilio Andrade,Cassão Victor,Ferrassini Luís Gustavo Barichello,Miyoshi Newton Shydeo Brandão,Alves Domingos,de Oliveira Lariza Laura

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Elsevier BV

Subject

General Engineering

Reference27 articles.

1. Tuberculosis,2022

2. Global Tuberculosis Programme: The end TB strategy,2015

3. Identifying socioeconomic, epidemiological and operational scenarios for tuberculosis control in Brazil: an ecological study;Pelissari;BJM Open,2018

4. World Health Organization and others: Global tuberculosis report 2021 (2021)

5. Effect of the Bolsa Familia Programme on the outcome of tuberculosis treatment: a prospective cohort study;Oliosi;The Lancet,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimized tuberculosis classification system for chest X‐ray images: Fusing hyperparameter tuning with transfer learning approaches;Engineering Reports;2024-04-29

2. Identification of Mycobacterium Tuberculosis Employing VGG-16 Feature Extraction and Classification Using Prominent Machine Learning Classifiers on X-rays;Lecture Notes in Networks and Systems;2024