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INTEGRATION OF EPIDEMIOLOGY, PATHOLOGY, IMMUNOLOGY AND OUTCOMES IN COLORECTAL CANCER - ABSTRACT MACHINE LEARNING HAS THE POTENTIAL TO TRANSFORM PATHOLOGIC DIAGNOSIS AND TO ADDRESS VERY LIMITED ACCESSIBILITY OF EXPERT PAT

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INTEGRATION OF EPIDEMIOLOGY, PATHOLOGY, IMMUNOLOGY AND OUTCOMES IN COLORECTAL CANCER - ABSTRACT MACHINE LEARNING HAS THE POTENTIAL TO TRANSFORM PATHOLOGIC DIAGNOSIS AND TO ADDRESS VERY LIMITED ACCESSIBILITY OF EXPERT PATHOLOGY IN LOW-INCOME COUNTRIES. ROUTINE HISTOLOGY IMAGES OF SOLID TUMORS CONTAIN AN IMMENSE NUMBER OF VISUAL FEATURES THAT CAN BE EXTRACTED AND PROCESSED BY ARTIFICIAL INTELLIGENCE TOOLS LIKE MACHINE LEARNING, WHICH EXCELS AT BASIC IMAGE ANALYSIS TASKS SUCH AS TUMOR DETECTION. IN ADDITION, MACHINE LEARNING CAN ALSO PREDICT CLINICALLY RELEVANT FEATURES DIRECTLY FROM HISTOLOGY IM

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