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Found 6 papers, 0 papers with code
Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations
In the United States, primary open-angle glaucoma (POAG) is the leading cause of blindness, especially among African American and Hispanic individuals.
Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data
Electronic Health Record (EHR) data has been of tremendous utility in Artificial Intelligence (AI) for healthcare such as predicting future clinical events.
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
This has been a major issue for developing ML models for the coronavirus-disease 2019 (COVID-19) pandemic where data is highly imbalanced, particularly within electronic health records (EHR) research.
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records
In this work, we train a Heterogeneous Graph Model (HGM) on Electronic Health Record data and use the resulting embedding vector as additional information added to a Convolutional Neural Network (CNN) model for predicting in-hospital mortality.
Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure
Here we propose using the latest graph representation learning and embedding models to refine and complete biomedical knowledge graphs.
Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN
We present a multi-filtering Graph Convolution Neural Network (GCN) framework for network embedding task.
