I am forthcoming with each patient that I strive to be fair in my black lung determinations. This means I may or may not find black lung on their X-ray. But—black lung or not—I will do my best to help each patient reach the right diagnosis and get the right treatment. Striving to be fair helps build my credibility to inform politicians and policymakers who also care about issues impacting coal miners.
I am well aware than nearly everyone reading this issue of CHEST Advocates is not directly impacted by bias in black lung. Fortunately, this issue is focused on bias in many different forms, with broad applicability, as well as the research integrity and tools needed to study medicine free from these influences.
In the feature article, expert sources break down the different types of biases that are most prevalent in clinical research and the importance of diverse participant pools, publishing outlets, and funding sources. However, with the recent funding cuts seen at the federal level, many equity-focused projects have been limited. Grant recipients share how this is affecting their research—which ultimately trickles down to patient care.
Read about Judy Wawira Gichoya, MD, MS, FSIIM, Co-Director of the Healthcare AI, Innovation, and Translational Informatics Lab at Emory University, who shares practical advice on how to identify and reduce bias while utilizing artificial intelligence (AI) in scientific research and clinical applications.
Hear Heather A. Bimonte-Nelson, PhD, of Arizona State University, discuss in her own words how bias related to sex and gender presents a problematic scientific shortcoming. She also provides proof for why sex should be a critical variable studied in research.