Editorial: Trustworthy AI for healthcaredoi:10.3389/fdgth.2024.1427233Agafonov, OlegBabic, AleksandarSousa, SoniaAlagaratnam, SharminiFrontiers in Digital Health
This MOOC gives an introduction to trustworthy artificial intelligence and its application in healthcare. This includes modules on basics of artificial intelligence and an introduction to trustworthy and ethical applications of artificial intelligence. A
Daneshjou Lab Re-imagining healthcare with technology We are an inter-disciplinary group of scientists, physicians, and engineers interested in leveraging the power of artificial intelligence for healthcare. In this pursuit, we focus on fairness and trustworthiness....
Augmented Intelligence (AI) systems have the power to transform health care and bring us closer to the quadruple aim: enhancing patient experience, improvi
Learn how trustworthy AI is helping healthcare providers and payers bring equitable preventative care for their most vulnerable members.
which waspublished last year, “is designed to be a flexible ‘living document’ will enable us to maintain a continuous focus on these critically important dimensions of algorithmic healthcare,” according to Michael Pencina, PhD, a co-founder of the coalition and di...
Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and tran...
Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and tran...
Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and tran...
We elaborate on mechanisms and considerations to address those aspects or challenges, and define the roles and responsibilities of the different stakeholders involved in AI for ophthalmic care, i.e., AI developers, reading centers, healthcare providers, healthcare institutions, ophthalmological societies...