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An AI-Guided Data Centric Strategy to Detect and Mitigate Biases in Healthcare Datasets
The adoption of diagnosis and prognostic algorithms in healthcare has led to concerns about the perpetuation of bias against disadvantaged groups of individuals.
Disease Progression Modeling Workbench 360
In this work we introduce Disease Progression Modeling workbench 360 (DPM360) opensource clinical informatics framework for collaborative research and delivery of healthcare AI.
Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
While networks with explicit memory have been proposed recently, the discontinuities imposed by the discrete operations make such networks harder to train and require more supervision.
Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care
The proposed method is favorable for healthcare applications because in additional to improved prediction performance, relationships among the different risks and risk factors are also identified.
Regularized Co-Clustering with Dual Supervision
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surpris- ingly impressive performance improvements over traditional one-sided (row) clustering techniques.
