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AI in GI

AI in GI ‘will have durable impact on the practice of medicine’

Topic: AI in GI ‘will have durable impact on the practice of medicine’

Technology is always evolving and enacting change in the world of medicine.

In his presentation for the American Society for Gastrointestinal Endoscopy’s virtual GI Outlook conference, Sidhartha Sinha, MD, from the division of gastroenterology and hepatology at Stanford Medicine, highlighted advances in technology that will transform the way physicians practice medicine.

“I believe all of these [areas] will have durable impacts on the practice of medicine,” he said. “These, and others, have the potential to address some of the issues we face.”

AI for patient care

Artificial intelligence has been one the major areas for recent study at the intersection of health and technology. Sinha said that research on AI — whether through neural networks or machine learning — has grown in recent years. He said in there were upwards of 12,000 studies that explored artificial intelligence in medicine by 2019, compared with just a few hundred in 2010.

While there are already a number of AI diagnostic technologies already approved by the FDA in specialties like oncology and radiology, none have been approved in GI. However, researchers have explored how the technology might impact aspects of the specialty, including adenoma detection rate and survival analysis for different kinds of gastrointestinal cancers.

“High ADR reduce interval colorectal cancer. We know that,” Sinha said. “The vast majority of AI in GI has been focused on this issue.”

There have been 50 studies on using AI for the analysis of pre-cancerous and malignant lesions, including 48 that focused endoscopy, and a majority of those have looked specifically on colon polyps or cancer. Sinha said they have returned overall positive results with accuracy greater than 80%.

Additionally, separate randomized controlled trials showed that deep learning programs reduced blind spots in esophagogastroduodenoscopy and improved ADR in diagnostic colonoscopy, respectively.

In inflammatory bowel disease, Sinha said a machine learning model that used labs, imaging and endoscopy outperformed 6-TGN levels in predicting response to thiopurines. Other studies showed how AI could predict corticosteroid-free remission and identify patients with Crohn’s disease who might be at risk for disease progression or surgery with greater than 80% accuracy, Sinha said.

Topic Discussed: AI in GI ‘will have durable impact on the practice of medicine’

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