Applications of artificial intelligence in pancreatic and biliary diseases

被引:12
作者
Chen, Po-Ting [1 ]
Chang, Dawei [2 ]
Wu, Tinghui [2 ]
Wu, Ming-Shiang [3 ,4 ]
Wang, Weichung [2 ]
Liao, Wei-Chih [3 ,4 ]
机构
[1] Natl Taiwan Univ, Natl Taiwan Univ Hosp, Coll Med, Dept Med Imaging, Taipei, Taiwan
[2] Natl Taiwan Univ, Inst Appl Math Sci, Taipei, Taiwan
[3] Natl Taiwan Univ, Natl Taiwan Univ Hosp, Coll Med, Div Gastroenterol & Hepatol,Dept Internal Med, Taipei, Taiwan
[4] Natl Taiwan Univ, Coll Med, Internal Med, Taipei, Taiwan
关键词
Artificial intelligence; Biliary disease; Pancreas; DUCTAL ADENOCARCINOMA; TEXTURE ANALYSIS; EARLY RECURRENCE; PREDICTION; RADIOMICS; CHOLANGIOCARCINOMA; FEATURES;
D O I
10.1111/jgh.15380
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
The application of artificial intelligence (AI) in medicine has increased rapidly with respect to tasks including disease detection/diagnosis, risk stratification, and prognosis prediction. With recent advances in computing power and algorithms, AI has shown promise in taking advantage of vast electronic health data and imaging studies to supplement clinicians. Machine learning and deep learning are the most widely used AI methodologies for medical research and have been applied in pancreatobiliary diseases for which diagnosis and treatment selection are often complicated and require joint consideration of data from multiple sources. The aim of this review is to provide a concise introduction of the major AI methodologies and the current landscape of AI research in pancreatobiliary diseases.
引用
收藏
页码:286 / 294
页数:9
相关论文
共 53 条
[1]  
[Anonymous], 2017, IN P IEEE C COMPUTER
[2]   Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis [J].
Attiyeh, Marc A. ;
Chakraborty, Jayasree ;
Doussot, Alexandre ;
Langdon-Embry, Liana ;
Mainarich, Shiana ;
Gonen, Mithat ;
Balachandran, Vinod P. ;
D'Angelica, Michael I. ;
DeMatteo, Ronald P. ;
Jarnagin, William R. ;
Kingham, T. Peter ;
Allen, Peter J. ;
Simpson, Amber L. ;
Do, Richard K. .
ANNALS OF SURGICAL ONCOLOGY, 2018, 25 (04) :1034-1042
[3]   Noncontrast Radiomics Approach for Predicting Grades of Nonfunctional Pancreatic Neuroendocrine Tumors [J].
Bian, Yun ;
Zhao, Zengrui ;
Jiang, Hui ;
Fang, Xu ;
Li, Jing ;
Cao, Kai ;
Ma, Chao ;
Guo, Shiwei ;
Wang, Li ;
Jin, Gang ;
Lu, Jianping ;
Xu, Jun .
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2020, 52 (04) :1124-1136
[4]  
Breiman L., 2001, IEEE Trans. Broadcast., V45, P5
[5]   Prediction of Pancreatic Neuroendocrine Tumor Grade Based on CT Features and Texture Analysis [J].
Canellas, Rodrigo ;
Burk, Kristine S. ;
Parakh, Anushri ;
Sahani, Dushyant V. .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2018, 210 (02) :341-346
[6]   CT radiomics to predict high-risk intraductal papillary mucinous neoplasms of the pancreas [J].
Chakraborty, Jayasree ;
Midya, Abhishek ;
Gazit, Lior ;
Attiyeh, Marc ;
Langdon-Embry, Liana ;
Allen, Peter J. ;
Do, Richard K. G. ;
Simpson, Amber L. .
MEDICAL PHYSICS, 2018, 45 (11) :5019-5029
[7]   Preliminary study of tumor heterogeneity in imaging predicts two year survival in pancreatic cancer patients [J].
Chakraborty, Jayasree ;
Langdon-Embry, Liana ;
Cunanan, Kristen M. ;
Escalon, Joanna G. ;
Allen, Peter J. ;
Lowery, Maeve A. ;
O'Reilly, Eileen M. ;
Gonen, Mithat ;
Do, Richard G. ;
Simpson, Amber L. .
PLOS ONE, 2017, 12 (12)
[8]   Deep Learning: A Primer for Radiologists [J].
Chartrand, Gabriel ;
Cheng, Phillip M. ;
Vorontsov, Eugene ;
Drozdzal, Michal ;
Turcotte, Simon ;
Pal, Christopher J. ;
Kadoury, Samuel ;
Tang, An .
RADIOGRAPHICS, 2017, 37 (07) :2113-2131
[9]   Applications of artificial intelligence in pancreatic and biliary diseases [J].
Chen, Po-Ting ;
Chang, Dawei ;
Wu, Tinghui ;
Wu, Ming-Shiang ;
Wang, Weichung ;
Liao, Wei-Chih .
JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY, 2021, 36 (02) :286-294
[10]   Utility of CT Radiomics Features in Differentiation of Pancreatic Ductal Adenocarcinoma From Normal Pancreatic Tissue [J].
Chu, Linda C. ;
Park, Seyoun ;
Kawamoto, Satomi ;
Fouladi, Daniel F. ;
Shayesteh, Shahab ;
Zinreich, Eva S. ;
Graves, Jefferson S. ;
Horton, Karen M. ;
Hruban, Ralph H. ;
Yuille, Alan L. ;
Kinzler, Kenneth W. ;
Vogelstein, Bert ;
Fishman, Elliot K. .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2019, 213 (02) :349-357