Predicting the Need for Therapeutic Intervention and Mortality in Acute Pancreatitis: A Two-Center International Study Using Machine Learning.

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Title

Predicting the Need for Therapeutic Intervention and Mortality in Acute Pancreatitis: A Two-Center International Study Using Machine Learning.

Content partner

The University of Auckland Library

Collection

ResearchSpace@Auckland

Description

BackgroundCurrent approaches to predicting intervention needs and mortality have reached 65-85% accuracy, which falls below clinical decision-making requirements in patients with acute pancreatitis (AP). We aimed to accurately predict therapeutic intervention needs and mortality on admission, in AP patients, using machine learning (ML).MethodsData were obtained from three databases of patients admitted with AP: one retrospective (Chengdu) and two prospective (Liverpool and Chengdu) databases....

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Format

Research paper

Research format

Journal article

Date created

2022-04

Creator

Shi, Na / Lan, Lan / Luo, Jiawei / Zhu, Ping / Ward, Thomas RW / Szatmary, Peter / Sutton, Robert / Huang, Wei / Windsor, John A / Zhou, Xiaobo / Xia, Qing

URL

https://hdl.handle.net/2292/62976

Related subjects

acute pancreatitis / interventions / machine learning / mortality / predictor / Patient Safety / 7.3 Management and decision making / 4.1 Discovery and preclinical testing of markers and technologies / 4 Detection, screening and diagnosis / 4.2 Evaluation of markers and technologies / 7 Management of diseases and conditions / 3 Good Health and Well Being / Science & Technology / Life Sciences & Biomedicine / Health Care Sciences & Services / Medicine, General & Internal / General & Internal Medicine / MINIMAL ACCESS RETROPERITONEAL / APACHE-II SCORE / ORGAN FAILURE / BIG DATA / SEVERITY / NECROSECTOMY / GUIDELINES / MARKERS / DYSFUNCTION / MANAGEMENT

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