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DySurv: Dynamic Deep Learning Model for Survival Prediction in the ICU
Survival analysis focuses on estimating time-to-event distributions which can help in dynamic risk prediction in healthcare.
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
To ensure trust and reliability in AI systems, especially in clinical risk prediction models, explainability becomes crucial.
XMI-ICU: Explainable Machine Learning Model for Pseudo-Dynamic Prediction of Mortality in the ICU for Heart Attack Patients
Heart attack remain one of the greatest contributors to mortality in the United States and globally.
Cluster-based Feature Importance Learning for Electronic Health Record Time-series
The recent availability of Electronic Health Records (EHR) has allowed for the development of algorithms predicting inpatient risk of deterioration and trajectory evolution.
Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease
Recent years have seen an increased focus into the tasks of predicting hospital inpatient risk of deterioration and trajectory evolution due to the availability of electronic patient data.
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
Accurate and reliable prediction of hospital admission location is important due to resource-constraints and space availability in a clinical setting, particularly when dealing with patients who come from the emergency department.
