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.CV2024★ 6 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.CL2024★ 51 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.LG2024★ 132 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…