A call for greater transparency, reproducibility in use of artificial intelligence in medicine

Boston, MA – Scientists working at the intersection of Artificial Intelligence (AI) and cancer care need to be more transparent about their methods and publish research that is reproducible, according to a new commentary co-authored by John Quackenbush, Henry Pickering Walcott Professor of Computational Biology and Bioinformatics and chair of the Department of Biostatistics at Harvard T.H. Chan School of Public Health. "The foundation of the scientific method is that research results must be testable by others. Testability is even more important in clinical applications because we need a high level of confidence in our methods before they are used with patients," Quackenbush said. "In applications of Artificial Intelligence, this requires that the models, software code, and data are available for independent validation. Transparency will accelerate research, advance patient care, and will build confidence among scientists and clinicians."