Advances in computer science and data-analytic methods are driving a new era in mental
health research and application. Artificial intelligence (AI) technologies hold the potential to …

The significant advancements in applying artificial intelligence (AI) to healthcare decision-
making, medical diagnosis, and other domains have simultaneously raised concerns about …

The emergence and increasing use of artificial intelligence and machine learning (AI/ML) in
healthcare practice and delivery is being greeted with both optimism and caution. We focus …

The adoption of artificial intelligence (AI) algorithms is rapidly increasing in healthcare. Such
algorithms may be shaped by various factors such as social determinants of health that can …

Effective implementation of artificial intelligence in behavioral healthcare delivery depends
on overcoming challenges that are pronounced in this domain. Self and social stigma …

As more industries integrate machine learning into socially sensitive decision processes like
hiring, loan-approval, and parole-granting, we are at risk of perpetuating historical and …

Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic
research discovery to individual health assessment. It is critical that these advances in …

Artificial intelligence (AI) shows promise for improving basic and translational science,
medicine, and public health, but its success is not guaranteed. Numerous examples have …

Mitigating Racial Bias in Machine Learning Page 1 92 journal of law, medicine & ethics The
Journal of Law, Medicine & Ethics, 50 (2022): 92-100. © 2022 The Author(s) DOI: https://doi.org/10.1017/jme.2022.13 …

Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the
fairness of such data-driven insights remains a concern in high-stakes fields. Despite …