DEVELOPMENT AND VALIDATION OF A MACHINE LEARNING TOOL FOR EARLY DIAGNOSIS OF INFLAMMATORY BOWEL DISEASE IN THE PRIMARY CARE SETTING: A POPULATION BASED STUDY

Although 3,000,000 Americans are afflicted with Inflammatory Bowel Disease (IBD) encompassing Crohn’s Disease (CD) and Ulcerative Colitis (UC)1, timely diagnosis is a challenge due to non-specific and overlapping symptoms.2 More than 20% of patients may be initially misdiagnosed3 causing delayed diagnosis and treatment, potentially leading to increased risk of complications2 and irreversible mucosal damage.4 Artificial intelligence (AI) models can alert physicians to patients who would otherwise be misdiagnosed, potentially improving patient outcomes and reducing costs.

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