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

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
  7. Xu Z, Zhang K, Liu D, Fang X. Predicting mortality and risk factors of sepsis related ARDS using machine learning models. Scientific Reports 2025;15(1) View
  8. Yang J, Zeng S, Cui S, Zheng J, Wang H. Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2025;27:e66615 View
  9. Cao Y, Wang Q, Wang X, Peng D, Li P. Multi-Gate Mixture of Multi-View Graph Contrastive Learning on Electronic Health Record. IEEE Journal of Biomedical and Health Informatics 2025;29(6):3956 View
  10. Lopes S, Mascarenhas M, Fonseca J, Fernandes M, Leite-Moreira A. Artificial Intelligence in Thoracic Surgery: Transforming Diagnostics, Treatment, and Patient Outcomes. Diagnostics 2025;15(14):1734 View
  11. Lange M, Chen Y, Fu H, Korada A, Guo C, Ma Y. CalTrig: A GUI-Based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents. eneuro 2025;12(7):ENEURO.0009-25.2025 View

Conference Proceedings

  1. Tsien E, Wu D, Fede A. 2023 IEEE 11th International Conference on Healthcare Informatics (ICHI). Developing Multi-Task Learning Methods to Aid in Electronic Healthcare Prediction View
  2. Tsien E, Wu D, Tong Y, Fede A, Gareau S. 2023 IEEE 11th International Conference on Healthcare Informatics (ICHI). Introducing Task-Adaptive Loss to Multitask Learning for Electronic Healthcare Prediction View