Diagnosing Hirschsprung disease, a condition that affects how waste moves through the bowel, requires precision. New research looked at how machine learning—a type of artificial intelligence—can assist doctors in identifying this condition using different imaging and tissue tests.
When looking at barium enema studies (an X-ray test), machine learning showed high accuracy for both finding the disease and correctly identifying those without it. In cases involving rectal biopsies, where doctors look at tissue samples under a microscope, machine learning appeared to speed up the time it takes to interpret results.
While these results are encouraging, the evidence is still early. The study included data from different sources that varied greatly in design and method. Because of this variety, experts say machine learning should currently be seen as a tool to help doctors work more efficiently rather than a replacement for expert human judgment.
