Published on in Vol 2 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/40755, first published
.
Patient Embeddings From Diagnosis Codes for Health Care Prediction Tasks: Pat2Vec Machine Learning Framework
Patient Embeddings From Diagnosis Codes for Health Care Prediction Tasks: Pat2Vec Machine Learning Framework
Journals
- El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
- Tansitpong P. Probabilistic Model of Patient Classification Using Bayesian Model. International Journal of Reliable and Quality E-Healthcare 2024;13(1):1 View
- Shakya P, Khaneja A, Wagholikar K. Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation. JMIR Medical Informatics 2025;13:e73020 View
- Steiger E, Kroll L. Patient Embeddings From Diagnosis Codes for Health Care Prediction Tasks: Pat2Vec Machine Learning Framework. JMIR AI 2023;2:e40755 View
Conference Proceedings
- Guyomard M, Bouhnik A, Tassy L, Urena R. 2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS). Encoding breast cancer patients’ medical pathways from reimbursement data using representation learning: a benchmark for clustering tasks View
- Kandasamy N, Basukoski A, Chaussalet T. 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS). A Comparative Analysis of Clustering Methods for Identifying Patient Subgroups in Chronic Kidney Disease Using Feature Engineering View