We must build safeguards against AI’s most dangerous feature: its ability to stop us thinking critically.

AI & Faith Dialogues

The h index is a widely recognized metric for assessing the research impact of scholars, defined as the maximum value h such that the scholar has published h papers each cited at least h times. While ...

In 1665, Newton's plague-driven isolation yielded calculus, universal gravitation, and revolutionary optics. Today's scientific enterprise produces more papers monthly than Newton's entire century, ye...

Academic laboratories face mounting resource constraints: budgets are tightening, grant overheads are potentially being capped, and the market rate for data-science talent significantly outstrips univ...

Collaborative Solutions for the Future of Healthcare

Objectives To investigate whether machine learning (ML) algorithms can learn racial or ethnic information from the vital signs alone.Methods A retrospective cohort study of critically ill patients bet...

The Language/AI Incubator, a cross-disciplinary, MITHIC-funded project, investigates how artificial intelligence can improve communications among patients and practitioners.

Artificial intelligence (AI) is one of the world's most resource-intensive digital technologies, but the environmental impact of AI on health remains …

aluation in line with contemporary healthcare settings and regional considerations. OBJECTIVES: To evaluate the geographic and temporal generalizability of the models for mortality prediction in IC...

Despite the rapid integration of AI in healthcare, a critical gap exists in current machine learning courses: the lack of education on identifying and mitigating bias in datasets. This oversight risks perpetuating existing health disparities through ...

There are models to predict intraoperative hypotension from arterial pressure waveforms. Selection bias in datasets used for model development and val…

The development of artificial intelligence (AI) applications in healthcare is often positioned as a solution to the greatest challenges facing global health. Advocates propose that AI can bridge gaps ...

Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death among women worldwide. Artificial intelligence (AI) s…

Background Variability in the provision of intensive care unit (ICU)-interventions may lead to disparities between socially defined racial-ethnic groups. Research Question We used causal inference to...

Many countries around the world do not collect race and ethnicity data in clinical settings. Without such identified data, it is difficult to identify…

On the evening of July 18, 2024, I began my shift in the cardiac intensive care unit, preparing for 12 hours as the unit charge nurse. I logged into our electronic medical record (EMR), printed my rep...

Author summary Bias in medical artificial intelligence (AI) systems refers to systematic errors that unfairly favor or disadvantage certain groups or outcomes. While often attributed to data quality i...

Background The deployment of Artificial Intelligence (AI) in healthcare has the potential to transform patient care through improved diagnostics, personalized treatment plans, and more efficient resou...

The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health inequalities. Within healthcare settings, large EHR datasets have increasingly enabled the use of ma...

Objectives Health research that significantly impacts global clinical practice and policy is often published in high-impact factor (IF) medical journals. These outlets play a pivotal role in the world...