most citedHeart disease risk prediction using deep learning techniques with feature augmentation

132 citations · 189 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CR2026

Influence of Autoencoder Latent Space on Classifying IoT CoAP Attacks

María Teresa García-Ordás, Jose Aveleira-Mata, Isaías García-Rodríguez +3

The Internet of Things (IoT) presents a unique cybersecurity challenge due to its vast network of interconnected, resource-constrained devices. These vulnerabilities not only threa…

cs.CV20246 cited

TEDNet: Twin Encoder Decoder Neural Network for 2D Camera and LiDAR Road Detection

Martín Bayón-Gutiérrez, María Teresa García-Ordás, Héctor Alaiz Moretón +3

Robust road surface estimation is required for autonomous ground vehicles to navigate safely. Despite it becoming one of the main targets for autonomous mobility researchers in rec…

cs.CL202451 cited

Enhancing ASD detection accuracy: a combined approach of machine learning and deep learning models with natural language processing

Sergio Rubio-Martín, María Teresa García-Ordás, Martín Bayón-Gutiérrez +2

Purpose: Our study explored the use of artificial intelligence (AI) to diagnose autism spectrum disorder (ASD). It focused on machine learning (ML) and deep learning (DL) to detect…

cs.LG2024132 cited

Heart disease risk prediction using deep learning techniques with feature augmentation

María Teresa García-Ordás, Martín Bayón-Gutiérrez, Carmen Benavides +2

Cardiovascular diseases state as one of the greatest risks of death for the general population. Late detection in heart diseases highly conditions the chances of survival for patie…