Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular, ...
A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients ...
Machine learning models using patient-reported outcomes, wearables, and clinical data accurately predicted urgent care visits ...
External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases Patient-level data from the ...
Enhancing the Quality of Hierarchic Relations in the National Cancer Institute Thesaurus to Enable Faceted Query of Cancer Registry Data We developed TransPRECISE (personalized cancer-specific ...
Introduction: The diagnosis of chronic obstructive pulmonary disease (COPD) is based on spirometry tests, which are difficult to perform in some populations. Objectives: We aimed to construct a risk ...
A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...
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