aimedlab Goto Github PK
Name: AIMed Lab @ OSU
Type: Organization
Bio: Artificial Intelligence in Medicine
Twitter: AIMedLab
Location: The Ohio State University
Blog: http://aimedlab.net/
Name: AIMed Lab @ OSU
Type: Organization
Bio: Artificial Intelligence in Medicine
Twitter: AIMedLab
Location: The Ohio State University
Blog: http://aimedlab.net/
Code and Datasets for the paper "A Computational Framework for Identifying Age Risks in Drug-Adverse Event Pairs", published on AMIA 2022 Informatics Summit.
Code and Datasets for the paper "Brain atlas guided attention u-net for white matter hyperintensity segmentation", published on AMIA 2021 Informatics Summit.
Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations"
Code and Datasets for the paper "Predicting Age-Related Macular Degeneration Progression with Contrastive Attention and Time-Aware LSTM", published on KDD 2022.
Code for the paper "Clinical connectivity map for drug repurposing: using laboratory results to bridge drugs and diseases". Accepted by BMC Medical Informatics and Decision Making, 2021
Code and Datasets for the paper "Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing", published on Patterns in 2022.
Code and Datasets for the paper "Combining structured and unstructured data for predictive models: a deep learning approach", published on BMC Medical Informatics and Decision Making in 2020.
Code and Datasets for the paper "Deconfounding actor-critic network with policy adaptation for dynamic treatment regimes", published on KDD 2022.
Code and Datasets for the paper "A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing", published on Nature Machine Intelligence in 2021.
Datasets for the paper "DeepDRiD: Diabetic Retinopathy—Grading and Image Quality Estimation Challenge", published on Patterns 2022.
Code and Datasets for the paper "A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data", published on Nature Machine Intelligence in 2021.
Code and Datasets for the paper "Domain Knowledge Guided Deep Learning with Electronic Health Records", published on ICDM 2019.
Code and Datasets for the paper "DG-Viz: Deep Visual Analytics with Domain Knowledge Guided Recurrent Neural Networks on Electronic Health Records", published on Journal of Medical Internet Research (JMIR) in 2020.
One of the top solutions for The 2019 DII National Data Science Challenge: https://sbmi.uth.edu/dii-challenge/. More details in the paper "An interpretable deep-learning model for early prediction of sepsis in the emergency department", published on Patterns 2021.
Code and Datasets for the paper "Estimating Individual Treatment Effects with Time-Varying Confounders", published on ICDM 2020.
Code and Datasets for the paper "Interpretable deep learning for automatic diagnosis of 12-lead electrocardiogram", published on iScience in 2021.
Code for the paper "FAME: Fragment-based Conditional Molecular Generation for Phenotypic Drug Discovery", published on SDM 2022.
Fairness and Accuracy Transfer by Density Matching
Code and Datasets for the paper "Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports", published on BMC Medical Informatics and Decision Making in 2019.
Code for the paper "Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning", published on ICDM 2021.
Code and Datasets for the paper "An Interpretable Risk Prediction Model for Healthcare with Pattern Attention", published on BMC Medical Informatics and Decision Making.
Code for paper "Estimating Trustworthy Treatment Effects for Antibiotic Stewardship in Sepsis"
Code and Datasets for the paper "Identifying Sepsis Subphenotypes via Time-Aware Multi-ModalAuto-Encoder", published on KDD 2020.
Code for the paper "Temporal clustering with external memory network for disease progression modeling". Accepted by ICDM 2021.
Code and Datasets for the paper "TransICD: Transformer Based Code-wise Attention Model for Explainable ICD Coding", accepted by AIME 2021.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.