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

Clinical Information and Decision Making (1412) Machine Learning (1473) Decision Support for Health Professionals (1191) Artificial Intelligence (1379)

Published on in Vol 23, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26139, first published .
Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study

Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study

Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study

Authors of this article:

Richard John Woodman1 Author Orcid Image ;   Kimberley Bryant1 Author Orcid Image ;   Michael J Sorich1 Author Orcid Image ;   Alberto Pilotto2, 3 Author Orcid Image ;   Arduino Aleksander Mangoni1 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Xu Z, Guo K, Chu W, Lou J, Chen C. Performance of Machine Learning Algorithms for Predicting Adverse Outcomes in Community-Acquired Pneumonia. Frontiers in Bioengineering and Biotechnology 2022;10 View
  2. Zampino M, Polidori M, Ferrucci L, O’Neill D, Pilotto A, Gogol M, Rubenstein L. Biomarkers of aging in real life: three questions on aging and the comprehensive geriatric assessment. GeroScience 2022;44(6):2611 View
  3. Cai W, Xu J, Chen Y, Wu X, Zeng Y, Yu F. Performance of Machine Learning Algorithms for Predicting Disease Activity in Inflammatory Bowel Disease. Inflammation 2023;46(4):1561 View
  4. Woodman R, Mangoni A. A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future. Aging Clinical and Experimental Research 2023;35(11):2363 View
  5. Loutati R, Ben-Yehuda A, Rosenberg S, Rottenberg Y. Multimodal Machine Learning for Prediction of 30-Day Readmission Risk in Elderly Population. The American Journal of Medicine 2024;137(7):617 View
  6. Chen Y, Lin F, Wang K, Chen F, Wang R, Lai M, Chen C, Wang R. Development of a predictive model for 1-year postoperative recovery in patients with lumbar disk herniation based on deep learning and machine learning. Frontiers in Neurology 2024;15 View
  7. Gebreyohannes E, Taye W, Shibe B, Ayele E, Lee K, Mengistu S, Soiza R, Myint P, Abdela O. Anticholinergic burden among in-patients: a cross-sectional study on prevalence, determinants, and impact on mortality in Ethiopia. Therapeutic Advances in Drug Safety 2024;15 View
  8. Wang X, Sun J, Zhang X, Chen W, Cao J, Hu H. Metagenomics reveals unique gut mycobiome biomarkers in psoriasis. Skin Research and Technology 2024;30(7) View
  9. Cai W, Wu X, Chen Y, Chen J, Lin X. Risk Factors and Prediction of 28-Day-All Cause Mortality Among Critically Ill Patients with Acute Pancreatitis Using Machine Learning Techniques: A Retrospective Analysis of Multi-Institutions. Journal of Inflammation Research 2024;Volume 17:4611 View
  10. Liu J, Duan X, Duan M, Jiang Y, Mao W, Wang L, Liu G. Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Cella A, Barbagelata M, Pilotto A. Gerontechnology. A Clinical Perspective. View
  2. Woodman R, Mangoni A. Gerontechnology. A Clinical Perspective. View
  3. Pilotto A, Volta E, Barbagelata M, Custodero C. Gerontechnology. A Clinical Perspective. View