Artificial intelligence predicts direct-acting antivirals failure among hepatitis C virus patients: A nationwide hepatitis C virus registry program

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1-3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning...

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Veröffentlicht in:	Clinical and molecular hepatology 2024-01, Vol.30 (1), p.64
Hauptverfasser:	Ming-ying Lu, Chung-feng Huang, Chao-hung Hung, Chi-ming Tai, Lein-ray Mo, Hsing-tao Kuo, Kuo-chih Tseng, Ching-chu Lo, Ming-jong Bair, Szu-jen Wang, Jee-fu Huang, Ming-lun Yeh, Chun-ting Chen, Ming-chang Tsai, Chien-wei Huang, Pei-lun Lee, Tzeng-hue Yang, Yi-hsiang Huang, Lee-won Chong, Chien-lin Chen, Chi-chieh Yang, Sheng-shun Yang, Pin-nan Cheng, Tsai-yuan Hsieh, Jui-ting Hu, Wen-chih Wu, Chien-yu Cheng, Guei-ying Chen, Guo-xiong Zhou, Wei-lun Tsai, Chien-neng Kao, Chih-lang Lin, Chia-chi Wang, Ta-ya Lin, Chih-lin Lin, Wei-wen Su, Tzong-hsi Lee, Te-sheng Chang, Chun-jen Liu, Chia-yen Dai, Jia-horng Kao, Han-chieh Lin, Wan-long Chuang, Cheng-yuan Peng, Chun-wei-tsai, Chi-yi Chen, Ming-lung Yu
Format:	Artikel
Sprache:	kor
Schlagworte:	Algorithms Antiviral agents Artificial intelligence Hepatitis C virus Machine learning
Online-Zugang:	Volltext
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