The analysed data could allow gastroenterologists to improve patient management.

“Typically, gastroenterologists have to rely on patient self-reported information about their stool to help determine the cause of their gastrointestinal health issues, which can be very unreliable,” explains Deborah Fisher, professor of medicine at Duke University Durham in North Carolina and a lead author on the study.

The results from the image analysis tool, which can be retrofitted in the pipes of an existing toilet, are encouraging.

It determines stool shape with 85% accuracy and detects blood with 76% accuracy.

To develop this technique, the researchers used more than 3,000 stool images found online or provided by research participants.

All images were annotated and classified using the Bristol Stool Scale method, which is frequently used to classify faecal matter.

This technique could help prevent inflammatory bowel disease and irritable bowel syndrome as well as ensure better patient follow-up after early diagnosis.

“This could be especially useful for patients who live in long-term care facilities who may not be able to report their conditions and could help improve initial diagnosis of acute conditions,” outlines Sonia Grego, a lead researcher on the study.

As for seeing the device installed in homes, the founder of the Duke Smart Toilet Lab is “optimistic,” pointing to the simplicity of the device for the patient.

This new technology can be installed in any existing toilet.

This device is still experimental at this stage and is not yet available to the general public.