Cabitza, Parimbelli

Let XAI generate reliability metadata, not medical explanations

Pubblicato in:  Computer Methods and Programs in Biomedicine

Santangelo, Nicora, Bellazzi, Dagliati

How good is your synthetic data? SynthRO, a dashboard to evaluate and benchmark synthetic tabular data

Peracchio, Nicora, Parimbelli, Buonocore, Dagliati, Bellazzi et al

RelAI: an automated approach to judge pointwise ML prediction reliability

Pubblicato in:  International Journal of Medical Informatics

Fasano et al

Towards the Identification of Patients’ Needs for Promoting Robotics and Allied Digital Technologies in Rehabilitation: A Systematic Review

Pubblicato in:  Healthcare

Nicora, Parimbelli, Quaglini et al.

Healthcare practitioners and robotic-assisted rehabilitation: understanding needs and barriers

Pubblicato in:  Journal of NeuroEngineering and Rehabilitation

Nicora, Pe, Santangelo, et al.

Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions

Pubblicato in:  Journal of NeuroEngineering and Rehabilitation

Pe, S. Famiglini, L., et al.

Alternative Strategies to Generate Class Activation Maps Supporting AI-based Advice in Vertebral Fracture Detection in X-ray Images

Pubblicato in:  MissingFormLabel Methods of Information in Medicine

Bergomi, L., Nicora, G., Orlowska, M.A. et al.

Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization

Pubblicato in:  BMC Medical Informatics and Decision Making