A study reveals AI’s struggle with tissue contamination in medical diagnostics, a problem easily managed by human pathologists, underscoring the importance of human expertise in healthcare despite advancements in AI technology.
“We train AIs to tell ‘A’ versus ‘B’ in a very clean, artificial environment, but, in real life, the AI will see a variety of materials that it hasn’t trained on. When it does, mistakes can happen,” said corresponding author Dr. Jeffery Goldstein, director of perinatal pathology and an assistant professor of perinatal pathology and autopsy at“Our findings serve as a reminder that AI that works incredibly well in the lab may fall on its face in the real world.
When humans examine tissue on slides, they can only look at a limited field within the microscope, then move to a new field, and so on. After examining the entire sample, they combine all the information they’ve gathered to make a diagnosis. An AI model performs in the same way, but the study found AI was easily misled by contaminants.