Vicomtech

Synthetic data generation for tabular health records: A systematic review

Mikel Hernandez, Gorka Epelde, Ane Alberdi et al.

2022 · 262 Zit.

Status and Recommendations of Technological and Data-Driven Innovations in Cancer Care: Focus Group Study

Haridimos Kondylakis, Cristian Axenie, Dhundy Bastola et al.

2020 · 21 Zit.

The role of artificial intelligence in implant dentistry: a systematic review

G Vázquez-Sebrango, Eduardo Anitua, Iván Macía et al.

2025 · 15 Zit.

Comprehensive evaluation framework for synthetic tabular data in health: fidelity, utility and privacy analysis of generative models with and without privacy guarantees

Mikel Hernandez, Pablo A. Osorio-Marulanda, Mikel Catalina et al.

2025 · 14 Zit.

Innovations in healthcare and medicine editorial

Manuel Graña, Darya Chyzhyk, Carlos Toro et al.

2016 · 4 Zit.

Neuralsentinel: Safeguarding Neural Network Reliability and Trustworthiness

Xabier Echeberria-Barrio, Mikel Gorricho, Selene Valencia et al.

2024 · 1 Zit.

Multicenter Prospective Blind External Validation of a Machine Learning Model for Predicting Heart Failure Decompensation: A 3-Hospital Validation Study

Jon Kerexeta, Esperança Lladó Pascual, Cristina Martín et al.

2024 · 1 Zit.

Synthetic Tabular Data Generation Under Horizontal Federated Learning Environments in Acute Myeloid Leukemia: Case-Based Simulation Study

Imanol Isasa, Mikel Catalina, Gorka Epelde et al.

2025 · 0 Zit.

Transformer-Based Architecture for Predicting Surgical Complications from EHR Data

E. E. Alonso, Naroa Mendez, Xabier Calle et al.

2026 · 0 Zit.

Development and validation of synthetic data generation over a federated learning computing framework to accelerate innovation and boost personalized medicine in hematological diseases

Gianluca Asti, Mattia Delleani, Patricia A. Apellániz et al.

2025 · 0 Zit.