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

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases ...

Medical algorithms routinely make decisions about patients’ health care, yet they are rife with bias. Health equity must be built into the development and deployment of these health algorithms.

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases ...

The race against Q-Day has begun, and success will require not just technical innovation, but the wisdom to learn from each ...

These included governance of algorithms, incorporation of design principles (including accountability, explainability, interpretability, transparency, and usability) into algorithm development and ...

Crowder told ET that the company is focusing on partnering with India in its National Quantum Mission and regional ...

At the same time, he’s struggling with the idea that the algorithms he’s writing may one day be biased against him—and even used against him—and is working to build a coalition of ...

At an international symposium to be held at the University at Buffalo May 5-6, algorithm developers and informatics researchers will explore the diffusion of evidence-based mental health treatment ...