A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...

Research from all publishers Recent studies have demonstrated how machine learning can be harnessed to cope with the expanding literature in evidence-based medicine.

AEquity aims to improve training for healthcare machine-learning algorithms by assessing the accuracy and fairness of the data they're fed.

Artificial Intelligence (AI) has rapidly turned into a healthcare buzzword. From smartphone apps that check your symptoms to sophisticated machine learning algorithms that forecast disease outcomes, ...

The symbiotic relationship between machine learning and chemistry holds the promise of unlocking insights and accelerating ...

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Artificial intelligence relies on machine learning algorithms trained on massive datasets to make predictions—think of how ...

The Machine Learning in Biomedicine (MLBioMed) research group at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, is currently seeking a highly-motivated postdoctoral ...