Ich stimme zu, dass diese Seite Cookies verwende. Weitere Informationen finden Sie unter unseren Datenschutzerklärungen .
X
Teixeira, Igor Vitor
1093  Ergebnisse:
Personensuche X
?
1

Predicting congenital syphilis cases: A performance evaluat..:

Teixeira, Igor Vitor ; da Silva Leite, Morgana Thalita ; de Morais Melo, Flávio Leandro...
PLOS ONE.  18 (2023)  6 - p. e0276150 , 2023
Link: https://doi.org/10.1371/..
 
?
2

Syphilis Trigram: a domain-specific visualisation to combat..:

de Morais, Cleber Matos ; Teixeira, Igor Vitor ; Sadok, Sara..
BMC Pregnancy and Childbirth.  22 (2022)  1 - p. , 2022
Link: https://doi.org/10.1186/..
 
?
3

A Comparative Study of Machine Learning Techniques for Mult..:

Tabosa de Oliveira, Thomás ; da Silva Neto, Sebastião Rogério ; Teixeira, Igor Vitor...
Frontiers in Tropical Diseases.  2 (2022)  - p. , 2022
Link: https://doi.org/10.3389/..
 
?
4

Machine learning and deep learning techniques to support cl..:

da Silva Neto, Sebastião Rogério ; Tabosa Oliveira, Thomás ; Teixeira, Igor Vitor...
PLOS Neglected Tropical Diseases.  16 (2022)  1 - p. e0010061 , 2022
Link: https://doi.org/10.1371/..
 
?
5

Binary Models for Arboviruses Classification Using Machine ..:

Da Silva Neto, Sebastião Rogerio ; Tabosa, Thomás ; Medeiros Neto, Leonides...
Proceedings of the 56th Hawaii International Conference on System Sciences.  , 2023
Link: https://hdl.handle.net/1..
 
?
6

Syphilis Trigram: a domain-specific visualisation to combat..:

de Morais, Cleber Matos ; Teixeira, Igor Vitor ; Sadok, Sara..
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9063215/.  , 2022
Link: http://www.ncbi.nlm.nih...
 
?
7

Predicting congenital syphilis cases: A performance evaluat..:

Igor Vitor Teixeira ; Morgana Thalita da Silva Leite ; Flávio Leandro de Morais Melo...
https://doi.org/10.1371/journal.pone.0276150.  , 2023
Link: https://doi.org/10.1371/..
 
?
8

Syphilis Trigram: a domain-specific visualisation to combat..:

Cleber Matos de Morais ; Igor Vitor Teixeira ; Sara Sadok..
https://doi.org/10.1186/s12884-022-04651-w.  , 2022
Link: https://doi.org/10.1186/..
 
?
9

Machine learning and deep learning techniques to support cl..:

Sebastião Rogério da Silva Neto ; Thomás Tabosa Oliveira ; Igor Vitor Teixeira...
https://doi.org/10.1371/journal.pntd.0010061.  , 2022
Link: https://doi.org/10.1371/..
 
?
10

Distribution of samples per classes:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/dataset/Distribution_of_samples_per_classes_/18340605.  , 2022
Link: https://doi.org/10.1371/..
 
?
11

Study selection:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/figure/Study_selection_/18340572.  , 2022
Link: https://doi.org/10.1371/..
 
?
12

Metrics used to evaluate the models proposed in the literat..:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/figure/Metrics_used_to_evaluate_the_models_proposed_in_the_literature_/18340590.  , 2022
Link: https://doi.org/10.1371/..
 
?
13

Summary of all demographic, epidemiological and clinical da..:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/dataset/Summary_of_all_demographic_epidemiological_and_clinical_data_presented_in_data_set_used_by_the_primary_studies_/18340611.  , 2022
Link: https://doi.org/10.1371/..
 
?
14

Attributes found in the data sets:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/figure/Attributes_found_in_the_data_sets_/18340584.  , 2022
Link: https://doi.org/10.1371/..
 
?
15

Characteristics of the data sets used to evaluate Machine L..:

Sebastião Rogério da Silva Neto (11944944) ; Thomás Tabosa Oliveira (11944947) ; Igor Vitor Teixeira (11944950)...
https://figshare.com/articles/dataset/Characteristics_of_the_data_sets_used_to_evaluate_Machine_Learning_and_Deep_Learning_models_for_arboviral_diseases_classification_/18340602.  , 2022
Link: https://doi.org/10.1371/..
 
1-15