SOTAVerified

Length-of-Stay prediction

Papers

Showing 1–10 of 28 papers

TitleStatusHype
Interpretable machine learning for time-to-event prediction in medicine and healthcareCode1
A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive CareCode1
Unsupervised Pre-Training on Patient Population Graphs for Patient-Level PredictionsCode1
Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge IntegrationCode1
X-CAL: Explicit Calibration for Survival AnalysisCode1
Predicting Patient Outcomes with Graph Representation LearningCode1
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care UnitCode1
Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional NetworksCode1
Multitask learning and benchmarking with clinical time series dataCode1
Equitable Length of Stay Prediction for Patients with Learning Disabilities and Multiple Long-term Conditions Using Machine Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EHR-Graph Transformer (pre-trained)Accuracy (LOS>3 Days)71.4—Unverified
2EHR-Graph TransformerAccuracy (LOS>3 Days)70.3—Unverified
3Random Forests (RF)Accuracy (LOS>3 Days)69.5—Unverified
4Logistic Regression (LR)Accuracy (LOS>3 Days)68.6—Unverified
5GRU-DAccuracy (LOS>3 Days)68.3—Unverified