Fernando Timoteo Fernandes
Overview
Explore the profile of Fernando Timoteo Fernandes including associated specialties, affiliations and a list of published articles.
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7
Citations
48
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Recent Articles
1.
Savalli C, Wichmann R, Filho F, Fernandes F, Porto Chiavegatto Filho A
PLOS Digit Health
. 2024 Dec;
3(12):e0000699.
PMID: 39723970
Machine learning (ML) is a promising tool in assisting clinical decision-making for improving diagnosis and prognosis, especially in developing regions. It is often used with large samples, aggregating data from...
2.
Wichmann R, Fernandes F, Porto Chiavegatto Filho A
Sci Rep
. 2023 Jan;
13(1):1022.
PMID: 36658181
Machine learning algorithms are being increasingly used in healthcare settings but their generalizability between different regions is still unknown. This study aims to identify the strategy that maximizes the predictive...
3.
Saito C, Bussacos M, Salvi L, Mensi C, Consonni D, Fernandes F, et al.
Int J Environ Res Public Health
. 2022 Jun;
19(11).
PMID: 35682539
In the original publication [...].
4.
Saito C, Bussacos M, Salvi L, Mensi C, Consonni D, Fernandes F, et al.
Int J Environ Res Public Health
. 2022 Mar;
19(6).
PMID: 35329341
The aim of this study is to compare the mortality rates for typical asbestos-related diseases (ARD-T: mesothelioma, asbestosis, and pleural plaques) and for lung and ovarian cancer in Brazilian municipalities...
5.
Fernandes F, Porto Chiavegatto Filho A
Rev Saude Publica
. 2021 Jun;
55:23.
PMID: 34133618
Objective: To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms. Methods: This...
6.
Fernandes F, Mendonca E Silva D, Campos F, Santana V, Cuani L, Curado M, et al.
Rev Bras Epidemiol
. 2021 Apr;
24:e210011.
PMID: 33825773
Objective: To develop a linkage algorithm to match anonymous death records of cancer of the larynx (ICD-10 C32X), retrieved from the Mortality Information System (SIM) and the Hospital Information System...
7.
A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil
Fernandes F, Oliveira T, Teixeira C, Batista A, Dalla Costa G, Porto Chiavegatto Filho A
Sci Rep
. 2021 Feb;
11(1):3343.
PMID: 33558602
The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially...