2021/04/21 by Jiasheng Cao, Ziyi Lu, Mingyu Chen +10 · 1 citation
Medicine · #Artificial intelligence #Colorectal Cancer Screening and Detection #Computer science #Hepatology #Internal medicine #MEDLINE #Medical physics #Medicine #Pancreatic and Hepatic Oncology Research #Radiology #Radiomics and Machine Learning in Medical Imaging
paper · doi:10.3748/wjg.v27.i16.1664
openalex publication_date 2021/04/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Originally proposed by John McCarthy in 1955, artificial intelligence (AI) has achieved a breakthrough and revolutionized the processing methods of clinical medicine with the increasing workloads of medical records and digital images. Doctors are paying attention to AI technologies for various diseases in the fields of gastroenterology and hepatology. This review will illustrate AI technology procedures for medical image analysis, including data processing, model establishment, and model validation. Furthermore, we will summarize AI applications in endoscopy, radiology, and pathology, such as detecting and evaluating lesions, facilitating treatment, and predicting treatment response and prognosis with excellent model performance. The current challenges for AI in clinical application include potential inherent bias in retrospective studies that requires larger samples for validation, ethics and legal concerns, and the incomprehensibility of the output results. Therefore, doctors and researchers should cooperate to address the current challenges and carry out further investigations to develop more accurate AI tools for improved clinical applications.