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Cited by in CrossRef
For: Uehara D, Hayashi Y, Seki Y, Kakizaki S, Horiguchi N, Tojima H, Yamazaki Y, Sato K, Yasuda K, Yamada M, Uraoka T, Kasama K. Non-invasive prediction of non-alcoholic steatohepatitis in Japanese patients with morbid obesity by artificial intelligence using rule extraction technology. World J Hepatol 2018; 10(12): 934-943 [PMID: 30631398 DOI: 10.4254/wjh.v10.i12.934]
URL: https://www.wjgnet.com/1948-5182/full/v10/i12/934.htm
Number Citing Articles
1
Yoichi Hayashi. The Right Direction Needed to Develop White-Box Deep Learning in Radiology, Pathology, and Ophthalmology: A Short ReviewFrontiers in Robotics and AI 2019; 6 doi: 10.3389/frobt.2019.00024
2
Yoichi Hayashi. New unified insights on deep learning in radiological and pathological images: Beyond quantitative performances to qualitative interpretationInformatics in Medicine Unlocked 2020; 19: 100329 doi: 10.1016/j.imu.2020.100329
3
Feifei Lu, Yao Meng, Xiaoting Song, Xiaotong Li, Zhuang Liu, Chunru Gu, Xiaojie Zheng, Yi Jing, Wei Cai, Kanokwan Pinyopornpanish, Andrea Mancuso, Fernando Gomes Romeiro, Nahum Méndez-Sánchez, Xingshun Qi. Artificial Intelligence in Liver Diseases: Recent AdvancesAdvances in Therapy 2024; 41(3): 967 doi: 10.1007/s12325-024-02781-5
4
Athanasios G. Pantelis, Georgios K. Stravodimos, Dimitris P. Lapatsanis. A Scoping Review of Artificial Intelligence and Machine Learning in Bariatric and Metabolic Surgery: Current Status and Future PerspectivesObesity Surgery 2021; 31(10): 4555 doi: 10.1007/s11695-021-05548-x
5
Athanasios G. Pantelis. Bariatric Surgery - Past and Present2023;  doi: 10.5772/intechopen.106365
6
Yoko Nagayasu, Daisuke Fujita, Masahide Ohmichi, Yoichi Hayashi. Use of an artificial intelligence‐based rule extraction approach to predict an emergency cesarean sectionInternational Journal of Gynecology & Obstetrics 2022; 157(3): 654 doi: 10.1002/ijgo.13888
7
Yoichi Hayashi. Artificial Intelligence and Machine Learning for Digital PathologyLecture Notes in Computer Science 2020; 12090: 95 doi: 10.1007/978-3-030-50402-1_6
8
Zhangfan Ye, Song Chen. Study on a New Sparse Rule Algorithm in Liver Disease2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI) 2020; : 33 doi: 10.1109/IICSPI51290.2020.9332314
9
Daisuke Uehara. Analysis of Diagnosis and Treatment Aimed at Improving the Prognosis of Non-viral Liver DiseaseThe Kitakanto Medical Journal 2023; 73(1): 113 doi: 10.2974/kmj.73.113
10
Pakanat Decharatanachart, Roongruedee Chaiteerakij, Thodsawit Tiyarattanachai, Sombat Treeprasertsuk. Application of artificial intelligence in non-alcoholic fatty liver disease and liver fibrosis: a systematic review and meta-analysisTherapeutic Advances in Gastroenterology 2021; 14: 175628482110628 doi: 10.1177/17562848211062807
11
Yogesh Kumar, Apeksha Koul, Ruchi Singla, Muhammad Fazal Ijaz. Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agendaJournal of Ambient Intelligence and Humanized Computing 2023; 14(7): 8459 doi: 10.1007/s12652-021-03612-z