Artificial Intelligence in Hepatology- Ready for the Primetime

被引:5
|
作者
Kalapala, Rakesh [1 ,3 ,4 ]
Rughwani, Hardik [1 ]
Reddy, D. Nageshwar [2 ]
机构
[1] Asian Inst Gastroenterol & AIG Hosp, Dept Gastroenterol, Hyderabad, India
[2] Asian Inst Gastroenterol & AIG Hosp, Hyderabad, India
[3] AIG Hosp, Int Bariatr & Metab Endoscopy Comm IFSO, Ctr Obes & Metab Therapy, Endoscopy, Hyderabad, India
[4] AIG Hosp, Cluster 1,1st Floor,Mindspace Rd, Hyderabad 500032, India
关键词
artificial intelligence; machine learning; deep learning; hepatol-ogy; NAFLD; LEARNING-BASED CLASSIFICATION; NEURAL-NETWORK; LIVER MASSES; HEPATITIS-C; RADIOMICS; FIBROSIS; MODELS;
D O I
10.1016/j.jceh.2022.06.009
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Artificial Intelligence (AI) is a mathematical process of computer mediating designing of algorithms to support human intelligence. AI in hepatology has shown tremendous promise to plan appropriate management and hence improve treatment outcomes. The field of AI is in a very early phase with limited clinical use. AI tools such as machine learning, deep learning, and 'big data' are in a continuous phase of evolution, presently being applied for clinical and basic research. In this review, we have summarized various AI applications in hepatology, the pitfalls and AI's future implications. Different AI models and algorithms are under study using clinical, laboratory, endoscopic and imaging parameters to diagnose and manage liver diseases and mass lesions. AI has helped to reduce human errors and improve treatment protocols. Further research and validation are required for future use of AI in hepatology. ( J CLIN EXP HEPATOL 2023;13:149-161)
引用
收藏
页码:149 / 161
页数:13
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