Blasimme, Alessandro

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

the Precise4Q consortium, Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020) · BMC Medical Informatics and Decision Making

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 2,203

Machine learning in medicine: Addressing ethical challenges

Vayena, E., Blasimme, A., & Cohen, I. G. (2018) · PLOS Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 912

The Ethics of AI in Biomedical Research, Patient Care and Public Health

Blasimme, A., & Vayena, E. (2019) · SSRN Electronic Journal

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 48

Familial Alzheimer's disease sustained by presenilin 2 mutations: Systematic review of literature and genotype–phenotype correlation

Canevelli, M., Piscopo, P., Talarico, G., Vanacore, N., Blasimme, A., Crestini, A., Tosto, G., Troili, F., Lenzi, G. L., Confaloni, A., et al. (2014) · Neuroscience & Biobehavioral Reviews

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 48

Sync fast and solve things-best practices for responsible digital health

Landers, C., Blasimme, A., & Vayena, E. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationBiomedical Ethics and Regulation

Cited by 35