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Novel Machine Learning Models Outperform Risk Scores in Predicting Hepatocellular Carcinoma in Patients with Chronic Viral Hepatitis by Grace Lai-Hung Wong; Vicki Wing-Ki Hui; Qingxiong Tan; Jingwen Xu; Hye Won Lee; Terry Cheuk-Fung Yip; Baoyao Yang; Yee-Kit Tse; Chong Yin; Fei Lyu; Jimmy Che-To Lai; Grace Chung-Yan Lui; Henry Lik-Yuen Chan; Pong-Chi Yuen; Vincent Wai-Sun Wong is a Medicine article available to read on EtoBox.
What is Novel Machine Learning Models Outperform Risk Scores in Predicting Hepatocellular Carcinoma in Patients with Chronic Viral Hepatitis about?
## Background & Aims Accurate hepatocellular carcinoma (HCC) risk prediction facilitates appropriate surveillance strategy and reduces cancer mortality. We aimed to derive and validate novel machine learning models to predict HCC in a territory-wide cohort of patients with chronic viral hepatitis (CVH) using data from the Hospital Authority Data Collaboration Lab (HADCL). ## Methods This was a territory-wide, retrospective, observational, cohort study of patients with CVH in Hong Kong in 2000–2018 identified from HADCL based on viral markers, diagnosis codes, and antiviral treatment for chronic hepatitis B and/or C. The cohort was randomly split into training and validation cohorts in a 7:3 ratio. Five popular machine learning methods, namely, logistic regression, ridge regression, AdaBoost, decision tree, and random forest, were performed and compared to find the best prediction model. ## Results A total of 124,006 patients with CVH with complete data were included to build the models. In the training cohort (n = 86,804; 6,821 HCC), ridge regression (area under the receiver operating characteristic curve [AUROC] 0.842), decision tree (0.952), and random forest (0.992) performed th
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- Author
- Grace Lai-Hung Wong; Vicki Wing-Ki Hui; Qingxiong Tan; Jingwen Xu; Hye Won Lee; Terry Cheuk-Fung Yip; Baoyao Yang; Yee-Kit Tse; Chong Yin; Fei Lyu; Jimmy Che-To Lai; Grace Chung-Yan Lui; Henry Lik-Yuen Chan; Pong-Chi Yuen; Vincent Wai-Sun Wong
- Publisher
- Elsevier BV
- Published
- 2022
- Language
- EN
- Field
- Medicine (Health Sciences)