Human pathologists are extensively trained to detect when tissue samples from one patient mistakenly end up on another patient's microscope slides (a problem known as tissue contamination). But such contamination can easily confuse artificial intelligence (AI) models, which are often trained in pristine, simulated environments, reports a new study. Each of the four AI models in the study paid too much attention to the tissue contamination, which resulted in errors when diagnosing or detecting vessel damage, gestational age, lesions and prostate cancer, the study found.