Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"
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Updated
Sep 13, 2024 - Python
Code for "Graph Neural Network on Electronic Health Records for Predicting Alzheimer’s Disease"
Electronic Health Record Analysis with Python.
Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Record
NER and Relation Extraction from Electronic Health Records (EHR).
[EMNLP'24] EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records
🧪Yet Another ICU Benchmark: a holistic framework for the standardization of clinical prediction model experiments. Provide custom datasets, cohorts, prediction tasks, endpoints, preprocessing, and models. Paper: https://arxiv.org/abs/2306.05109
FHIR Python Analysis Client and Kit (FHIRPACK) is a general purpose FHIR client that simplifies the access, analysis and representation of FHIR and EHR data using PANDAS, an ETL philosophy and a functional syntax. It was initially developed at the IKIM and HDDBS in Germany. Read more at https://zenodo.org/record/8006589
A Comprehensive Benchmark For COVID-19 Predictive Modeling Using Electronic Health Records
Code for the paper: Multi-Label Clinical Time-Series Generation via Conditional GAN (IEEE TKDE)
A Multimodal Transformer: Fusing Clinical Notes With Structured EHR Data for Interpretable In-Hospital Mortality Prediction
[ML4H 2022] This is the code for our paper `Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR'.
Natural language generation for discrete data in EHRs
attribute-based access control implementation for EHRs
COVID-19 EHR data analysis pipeline
Continual Learning of Electronic Health Records (EHR).
Thanks to digitization, we often have access to large databases, consisting of various fields of information, ranging from numbers to texts and even boolean values. Such databases lend themselves especially well to machine learning, classification and big data analysis tasks. We are able to train classifiers, using already existing data and use …
Convert arbitrary EHR extracts to FHIR.
"Modeling electronic health record data using an end-to-end knowledge-graph-informed topic model" paper on Sci Rep (2022)
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