Hospital de Galdakao

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

Edward De Brouwer, Thijs Becker, Yves Moreau et al.

2021 · 41 Zit.

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods

Fernando García-García, Dae‐Jin Lee, Francisco J. Mendoza-Garcés et al.

2024 · 12 Zit.

Cost-Sensitive Ordinal Classification Methods to Predict SARS-CoV-2 Pneumonia Severity

Fernando García-García, Dae‐Jin Lee, Pedro Pablo España et al.

2024 · 6 Zit.

Explainable time-to-progression predictions in multiple sclerosis

Robbe D’hondt, Klest Dedja, Sofie Aerts et al.

2025 · 5 Zit.

Generación masiva de historias clínicas sintéticas con ChatGPT: un ejemplo en fractura de cadera

Isidoro Calvo-Lorenzo, Iker Uriarte-Llano

2024 · 2 Zit.

Use of digital health tools in inflammatory bowel disease

Iago Rodríguez-Lago, Beatriz Gros, Kristy Sánchez et al.

2024 · 2 Zit.

Massive generation of synthetic medical records with ChatGPT: An example in hip fractures

Isidoro Calvo-Lorenzo, Iker Uriarte-Llano

2024 · 1 Zit.

Análisis de modelos algorítmicos de aprendizaje automático para la predicción del estado vital a los seis meses tras fractura de cadera en pacientes mayores de 74 años

Irineo Lorenzo, Iker Uriarte Llano, M.R. Mateo Citores et al.

2024 · 1 Zit.

Can mortality prediction be enhanced integrating patient clinical and medical imaging data?

Rodriguez-Idiazabal, Lander, Avalos, Marta, Quintana-Lopez, Jose M. et al.

2025 · 0 Zit.

[Translated article] Analysis of machine learning algorithmic models for the prediction of vital status at six months after hip fracture in patients older than 74 years

Irineo Lorenzo, Iker Uriarte Llano, M.R. Mateo Citores et al.

2024 · 0 Zit.