Japanese Scientists Focus Machine Learning on Histopathology Images
There has been another exciting medical breakthrough that is a direct result of a particular use of machine learning by two doctors from Japan. The article on identifying Crohn’s disease was published on scietechdaily.com.
According to researchers, more than 500,000 individuals in the United States have Crohn’s disease. Crohn’s disease is a chronic inflammatory bowel disease that damages the digestive system lining. It can cause digestive system inflammation, which may result in abdominal pain, severe diarrhea, exhaustion, weight loss, and malnutrition.
While medical procedures and operations can treat Crohn’s, it often returns in patients, according to a report from The American Journal of Pathology.
Now, researchers are reporting that their AI tool is highly accurate at predicting the postoperative recurrence of Crohn’s disease. It also linked recurrence with the histology of subserosal adipose cells and mast cell infiltration.
New AI Study on Post-Op Tissue
Using an AI tool that simulates how humans visualize and is trained to identify and categorize pictures, researchers created a model that predicts the postoperative recurrence of Crohn’s disease with high accuracy by evaluating histological or tissue images. The AI tool also identified previously unknown differences in adipose cells and substantial disparities in the degree of mast cell infiltration in the subserosa, or outer lining of the gut, when comparing individuals with and without disease recurrence.
See, it’s not a simple process to completely understand if you are a layman. But the results of the AI being utilized are pretty amazing.
“Most of the analysis of histopathological images using AI in the past have targeted malignant tumors,” explained lead investigators Takahiro Matsui, MD, Ph.D., and Eiichi Morii, MD, Ph.D., Department of Pathology, Osaka University Graduate School of Medicine, Osaka, Japan. “We aimed to obtain clinically useful information for a wider variety of diseases by analyzing histopathology images using AI. We focused on Crohn’s disease, in which postoperative recurrence is a clinical problem.”
Dr. Matsui and Dr. Morii explained how many patients they tested, how they created heat maps of tissues, and so much more detailed medical information regarding the machine learning they assigned to this project.
To the investigators’ knowledge, these findings are the first to link postoperative recurrence of Crohn’s disease with the histology of subserosal adipose cells and mast cell infiltration. Dr. Matsui and Dr. Morii observed, “Our findings enable stratification by the prognosis of postoperative Crohn’s disease patients. Many drugs, including biologicals, are used to prevent Crohn’s disease recurrence, and proper stratification can enable more intensive and successful treatment of high-risk patients.”
It’s an advance that could lead to more breakthroughs.
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