Suchergebnisse - "da Silva Rocha, Elisson"

On the usage of artificial intelligence in leprosy care: A systematic literature review.

Autoren: de Andrade, Hilson Gomes Vilar da Silva Rocha, Elisson de Carvalho Monteiro, Kayo H. et al.

Quelle: PLoS Computational Biology; 6/26/2025, Vol. 21 Issue 6, p1-34, 34p

Schlagwörter: HANSEN'S disease, NEGLECTED diseases, IMAGE recognition (Computer vision), CONVOLUTIONAL neural networks, MYCOBACTERIUM leprae

Utilization of tree-based machine learning models for predicting low birth weight cases.

Autoren: de Morais, Flavio Leandro da Silva Rocha, Elisson Masson, Gabriel et al.

Quelle: BMC Pregnancy & Childbirth; 2/26/2025, Vol. 25 Issue 1, p1-32, 32p

Schlagwörter: MACHINE learning, LOW birth weight, MATHEMATICAL statistics, PRENATAL care, STATISTICS

Benchmarking machine learning models to assist in the prognosis of tuberculosis

Autoren: da Silva Barros, Maicon Herverton Lino Ferreira Alves, Geovanne Oliveira Souza, Lubnnia Morais Florêncio et al.

Quelle: da Silva Barros, Maicon Herverton Lino Ferreira ORCID: 0000-0002-0275-3298 <

Index Begriffe: Machine learning, tuberculosis; neglected tropical disease; prognosis; ensemble model; imbalanced data sets; feature selection; random search; benchmark, Article, PeerReviewed

URL: http://doras.dcu.ie/27522/
http://doras.dcu.ie/27522/1/informatics-08-00027.pdf
http://doras.dcu.ie/27522/1/informatics-08-00027.pdf
https://dx.doi.org/10.3390/informatics8020027

Evaluating a deep learning model in integrated health databases to aid in the prognosis of tuberculosis.

Autoren: da Silva Leite, Morgana Thalita Lino Ferreira da Silva Barros, Maicon Herverton da Silva Rocha, Elisson et al.

Quelle: CISTI (Iberian Conference on Information Systems & Technologies / Conferência Ibérica de Sistemas e Tecnologias de Informação) Proceedings; 2023, Issue 18, p1-6, 6p

Schlagwörter: TUBERCULOSIS prognosis, DEEP learning, TUBERCULOSIS mortality, MEDICAL databases

Geografische Kategorien: BRAZIL

Benchmarking machine learning models to assist in the prognosis of tuberculosis

Autoren: da Silva Barros Maicon Herverton Lino Ferreira Alves, Geovanne Oliveira et al.

Quelle: da Silva Barros, Maicon Herverton Lino Ferreira orcid:0000-0002-0275-3298 , Alves, Geovanne Oliveira orcid:0000-0002-2084-5516 , Souza, Lubnnia Morais Florêncio orcid:0000-0002-2188-6272 , da Silva Rocha, Elisson orcid:0000-0002-7742-2995 , Oliveira, João Fausto Lorenzato de orcid:0000-0002-1150-4904 , Lynn, Theo orcid:0000-0001-9284-7580 , Sampaio, Vanderson orcid:0000-0001-7307-8851 and Takako Endo, Patricia orcid:0000-0002-9163-5583 (2021) Benchmarking machine learning models to assist in the prognosis of tuberculosis. Informatics, 8 (2). ISSN 2227-9709

Schlagwörter: Machine learning, tuberculosis, neglected tropical disease, prognosis, ensemble model, imbalanced data sets, feature selection, random search, benchmark

Relation: http://doras.dcu.ie/27522/1/informatics-08-00027.pdf; http://doras.dcu.ie/27522/

Verfügbarkeit: http://doras.dcu.ie/27522/1/informatics-08-00027.pdf
http://doras.dcu.ie/27522/

Benchmarking Machine Learning Models to Assist in the Prognosis of Tuberculosis.

Autoren: Lino Ferreira da Silva Barros, Maicon Herverton Oliveira Alves, Geovanne Morais Florêncio Souza, Lubnnia et al.

Quelle: Informatics; Jun2021, Vol. 8 Issue 2, p27-27, 1p

Schlagwörter: MEDICAL personnel, MACHINE learning, MYCOBACTERIUM tuberculosis, DATA scrubbing, PROGNOSIS, TUBERCULOSIS

Geografische Kategorien: AMAZONAS (Brazil)