A Triantafyllidis

From Trustworthy AI Principles to Verifiable System Requirements: A Multi-Stakeholder Engineering Framework for Clinical Decision Support Systems

Antonino Angi, Joan Perramon-Llussà, Ilia Stepin, Miriam Cabrita et autres

es, us, pt, tr, nl, gr, gb (code pays fourni par la source)

Big Data and Trustworthy AI for Heart Failure: A Review

Joan Perramon-Llussà, Grzegorz Skorupko, Shishir Rao, Esmeralda Ruiz Pujadas et autres

The rapid evolution of machine learning techniques, combined with the growing availability of large and diverse datasets, is poised to transform heart failure research and clinical care. This review first provides an overview of key machine learning and artificial intelligence concepts used …

es, gb, us, nl, gr (code pays fourni par la source)

Integrating participatory research and literature review to identify social and ethical requirements for responsible AI in heart failure treatment

Natália T. Machado, Harm op den Akker, Isabella Cinà, Joan Perramon Llussà et autres

The rapid advancement of Artificial Intelligence (AI) in healthcare raises significant social and ethical concerns, particularly in cardiovascular care, the leading cause of death worldwide. Addressing these challenges requires a multidisciplinary, multi-stakeholder approach to ensure the responsible development and implementation of AI-driven …

us, pt, be, es, nl, gr (code pays fourni par la source)

Integrating participatory research and literature review to identify social and ethical requirements for responsible AI in heart failure treatment

Natália T. Machado, Harm op den Akker, Isabella Cinà, Joan Perramon Llussà et autres

The rapid advancement of Artificial Intelligence (AI) in healthcare raises significant social and ethical concerns, particularly in cardiovascular care, the leading cause of death worldwide. Addressing these challenges requires a multidisciplinary, multi-stakeholder approach to ensure the responsible development and implementation of AI-driven …

us, pt, be, es, nl, gr (code pays fourni par la source)

The impact of artificial intelligence-driven risk prediction on clinical decisions in heart failure patients: the design of an international vignette study

J Ten Broeke, M J Boonstra, R W M Vernooij, A Triantafyllidis et autres

Abstract Background/introduction Heart failure (HF), affecting over 64 million people worldwide, is a complex syndrome that requires personalized treatment. [1] The use of risk prediction models may help guide tailored care and is recommended by international guidelines. [2] However, clinical utility and …

nl, gr, es, pe, cz, Tanzanie, pt (code pays fourni par la source)