Search Results for author:
Found 8 papers, 5 papers with code
Understanding Heart-Failure Patients EHR Clinical Features via SHAP Interpretation of Tree-Based Machine Learning Model Predictions
We examined whether machine learning models, more specifically the XGBoost model, can accurately predict patient stage based on EHR, and we further applied the SHapley Additive exPlanations (SHAP) framework to identify informative features and their interpretations.
Learning Latent Causal Structures with a Redundant Input Neural Network
We developed a deep learning model, which we call a redundant input neural network (RINN), with a modified architecture and a regularized objective function to find causal relationships between input, hidden, and output variables.
Supervised Vector Quantized Variational Autoencoder for Learning Interpretable Global Representations
When training a deep generative model, the observed data are often associated with certain categorical labels, and, in parallel with learning to regenerate data and simulate new data, learning an interpretable representation of each class of data is also a process of acquiring knowledge.
PubMedQA: A Dataset for Biomedical Research Question Answering
We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected from PubMed abstracts.
Ranked #7 on
Question Answering
on PubMedQA
Probing Biomedical Embeddings from Language Models
For this we use the pre-trained LMs as fixed feature extractors and restrict the downstream task models to not have additional sequence modeling layers.
From genome to phenome: Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer
Here, we present a deep neural network model with encoder-decoder architecture, referred to as genomic impact transformer (GIT), to infer the functional impact of SGAs on cellular signaling systems through modeling the statistical relationships between SGA events and differentially expressed genes (DEGs) in tumors.
AttentionMeSH: Simple, Effective and Interpretable Automatic MeSH Indexer
There are millions of articles in PubMed database.
