Mario Alejandro Bravo-Ortiz

Orcid: 0000-0003-3560-1300

According to our database1, Mario Alejandro Bravo-Ortiz authored at least 17 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Benchmarking of closed vision-language models for Ki-67 index prediction in breast cancer histopathology images.
Expert Syst. Appl., 2026

Detection of Carbapenem Resistance in Klebsiella pneumoniae Using Vision Transformers and MALDI-TOF Proteomic Profiles.
IEEE Access, 2026

2025
Predicting no-shows at outpatient appointments in internal medicine using machine learning models.
PeerJ Comput. Sci., 2025

Transformers and capsule networks <i>vs</i> classical ML on clinical data for alzheimer classification.
PeerJ Comput. Sci., 2025

R-SIT: A Swin-Transformer-Based Architecture for Spatial Image Steganalysis.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2025

2024
A systematic review of vision transformers and convolutional neural networks for Alzheimer's disease classification using 3D MRI images.
Neural Comput. Appl., December, 2024

A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure.
BMC Medical Informatics Decis. Mak., December, 2024

CVTStego-Net: A convolutional vision transformer architecture for spatial image steganalysis.
J. Inf. Secur. Appl., 2024

SpectroCVT-Net: A convolutional vision transformer architecture and channel attention for classifying Alzheimer's disease using spectrograms.
Comput. Biol. Medicine, 2024

2023
Classification of Alzheimer's disease stages from magnetic resonance images using deep learning.
PeerJ Comput. Sci., 2023

2022
Machine learning approaches for COVID-19 detection from chest X-ray imaging: A Systematic Review.
CoRR, 2022

Coffee Maturity Classification Using Convolutional Neural Networks and Transfer Learning.
IEEE Access, 2022

2021
Sensitivity of deep learning applied to spatial image steganalysis.
PeerJ Comput. Sci., 2021

Strategy to improve the accuracy of convolutional neural network architectures applied to digital image steganalysis in the spatial domain.
PeerJ Comput. Sci., 2021

Machine learning applications to predict two-phase flow patterns.
PeerJ Comput. Sci., 2021

GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis.
IEEE Access, 2021



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