Artificial intelligence can detect intestinal parasites in stool samples with greater accuracy than experienced laboratory technicians, according to research that could transform how labs diagnose parasitic infections worldwide.

Scientists at ARUP Laboratories and Utah startup Techcyte developed a deep-learning model that achieved 98.6 per cent agreement with manual microscopic examination whilst identifying 169 additional organisms that human reviewers had missed, reports the Journal of Clinical Microbiology.