This paper is in the following e-collection/theme issue:

Machine Learning (1501) Advanced Data Analytics in eHealth (142)

Published on in Vol 8, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24305, first published .
Machine-Learning Monitoring System for Predicting Mortality Among Patients With Noncancer End-Stage Liver Disease: Retrospective Study

Machine-Learning Monitoring System for Predicting Mortality Among Patients With Noncancer End-Stage Liver Disease: Retrospective Study

Machine-Learning Monitoring System for Predicting Mortality Among Patients With Noncancer End-Stage Liver Disease: Retrospective Study

Authors of this article:

Yu-Jiun Lin1, 2 Author Orcid Image ;   Ray-Jade Chen3, 4 Author Orcid Image ;   Jui-Hsiang Tang5 Author Orcid Image ;   Cheng-Sheng Yu1, 2 Author Orcid Image ;   Jenny L Wu1, 2 Author Orcid Image ;   Li-Chuan Chen6, 7 Author Orcid Image ;   Shy-Shin Chang1, 2, 6 Author Orcid Image
Article Authors Cited by (11) Tweetations (3) Metrics

Journals

  1. Surodina S, Lam C, Grbich S, Milne-Ives M, van Velthoven M, Meinert E. Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study. JMIRx Med 2021;2(2):e25560 View
  2. Chan Y, Chang S, Wu J, Wang S, Yu C. Association between liver stiffness measurement by transient elastography and chronic kidney disease. Medicine 2022;101(4):e28658 View
  3. Lu Y, Chao H, Chiang Y, Chen H. Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation. Journal of Medical Internet Research 2023;25:e43734 View
  4. Vu E, Steinmann N, Schröder C, Förster R, Aebersold D, Eychmüller S, Cihoric N, Hertler C, Windisch P, Zwahlen D. Applications of Machine Learning in Palliative Care: A Systematic Review. Cancers 2023;15(5):1596 View
  5. Sarmet M, Kabani A, Coelho L, dos Reis S, Zeredo J, Mehta A. The use of natural language processing in palliative care research: A scoping review. Palliative Medicine 2023;37(2):275 View
  6. Chiu K, Chen Y, Wang S, Chang T, Wu J, Shih C, Yu C. Exploring the Potential Performance of Fibroscan for Predicting and Evaluating Metabolic Syndrome using a Feature Selected Strategy of Machine Learning. Metabolites 2023;13(7):822 View
  7. Bürger V, Amann J, Bui C, Fehr J, Madai V. The unmet promise of trustworthy AI in healthcare: why we fail at clinical translation. Frontiers in Digital Health 2024;6 View
  8. Mafi V, Soldera J. Palliative care for end-stage liver disease and acute on chronic liver failure: A systematic review. World Journal of Methodology 2024;14(4) View
  9. Hsieh V, Liu M, Lin H. AI-Enabled Clinical Decision Support System Modeling for the Prediction of Cirrhosis Complications. IRBM 2024;45(5):100854 View

Books/Policy Documents

  1. Thamby B, Sheeja S. ICT Analysis and Applications. View