Method and diagnostic apparatus for determining enteric disorder using machine learning model

A diagnostic apparatus for diagnosing an enteric disorder by using a machine learning model, comprising:

• a microbial data extraction unit that extracts multiple microbial data based on an analysis result of a mixture of a gut-derived substance collected from a subject and a gut environment-like composition;
• a feature selection unit that selects a microbe-related feature to be used for the machine learning model from the multiple microbial data based on a predetermined feature selection algorithm;
• a training unit that trains the machine learning model by using the microbe-related feature;
• and
• a diagnostic unit that diagnoses an enteric disorder by inputting, into the trained machine learning model, the microbial data collected from a subject to be tested,
• wherein the microbe-related feature includes the content of at least one kind of microbes selected from genera belonging to the family Tannerellaceae, the family Bifidobacteriaceae, the family Ruminococcaceae, the family Clostridaceae, the family Lachnospiraceae, the family Bacteroidaceae, the family Erysipelatoclostridiaceae, the family Veilonellaceae, the family Bacteroidaceae, the family Ruminococcaceae, the family Lachnospiraceae, and the family Anaerovoracaceae.