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

Machine Learning (1501) Electronic Health Records (1068) Secondary Use of Clinical Data for Research and Surveillance (375) Decision Support for Health Professionals (1210)

Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36202, first published .
Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study

Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study

Multitask Learning With Recurrent Neural Networks for Acute Respiratory Distress Syndrome Prediction Using Only Electronic Health Record Data: Model Development and Validation Study

Authors of this article:

Carson Lam1 Author Orcid Image ;   Rahul Thapa1 Author Orcid Image ;   Jenish Maharjan1 Author Orcid Image ;   Keyvan Rahmani1 Author Orcid Image ;   Chak Foon Tso1 Author Orcid Image ;   Navan Preet Singh1 Author Orcid Image ;   Satish Casie Chetty1 Author Orcid Image ;   Qingqing Mao1 Author Orcid Image
Article Authors Cited by (8) Tweetations (14) Metrics

Journals

  1. Ge R, Wang F, Peng Z. Advances in Biomarkers for Diagnosis and Treatment of ARDS. Diagnostics 2023;13(21):3296 View
  2. Thapa R, Garikipati A, Ciobanu M, Singh N, Browning E, DeCurzio J, Barnes G, Dinenno F, Mao Q, Das R. Machine Learning Differentiation of Autism Spectrum Sub-Classifications. Journal of Autism and Developmental Disorders 2024;54(11):4216 View
  3. Pigat L, Geisler B, Sheikhalishahi S, Sander J, Kaspar M, Schmutz M, Rohr S, Wild C, Goss S, Zaghdoudi S, Hinske L. Predicting Hypoxia Using Machine Learning: Systematic Review. JMIR Medical Informatics 2024;12:e50642 View
  4. Tran T, Tran M, Joseph A, Phan P, Grau V, Farmery A. A systematic review of machine learning models for management, prediction and classification of ARDS. Respiratory Research 2024;25(1) View
  5. Sharafutdinov K, Fritsch S, Iravani M, Ghalati P, Saffaran S, Bates D, Hardman J, Polzin R, Mayer H, Marx G, Bickenbach J, Schuppert A. Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets. IEEE Open Journal of Engineering in Medicine and Biology 2024;5:611 View
  6. Rubulotta F, Bahrami S, Marshall D, Komorowski M. Machine Learning Tools for Acute Respiratory Distress Syndrome Detection and Prediction. Critical Care Medicine 2024;52(11):1768 View