This is a repository that collects machine learning papers on biomedical application.
- Review
- Phenotype
- NER-RE-KG
- Medical Concept Representation
- Cancer
- ECG
- Image Interpretation
- QA
- Readmission Rate
| Title | Year | Journal | Team |
|---|---|---|---|
| What Can Natural Language Processing do For Clinical Decision Support? | 2009 | Journal of Biomedical Informatics | Dina Fushman@NIH |
| Deep Learning for Health Informatics | 2017 | Journal of Biomedical and Health Informatics | 杨广中@ICL |
| Big Data for Health | 2015 | Journal of Biomedical and Health Informatics | 杨广中@ICL |
| Mining Electronic Health Records: Towards Better Research Applications and Clinical Care | 2012 | Nature Reviews Genetics | |
| A Review of Approaches to Identifying Patient Phenotype Cohorts Using Electronic Health Records | 2014 | JIMIA | |
| Machine Learning and Decision Support in Critical Care | 2016 | Proceedings of the IEEE | |
| Mining Electronic Health Records- A Survey | 2016 | ACM Computing Surveys |
| Title | Year | Journal | Team |
|---|---|---|---|
| Deep Patient－ An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records | 2016 | Scientific Reports | Riccardo Miotto /Joel T. Dudley@Icahn School of Medicine at Mount Sinai |
| Identification of type 2 diabetes subgroups through topological analysis of patient similarity | 2015 | Li Li /Joel T. Dudley@Icahn School of Medicine at Mount Sinai | |
| Doctor AI- Predicting Clinical Events via Recurrent Neural Networks | 2016 | JMLR | Edward Choi/Jimeng Sun@GIT |
| Deepr: A Convolutional Net for Medical Records | 2017 | Journal of Biomedical and Health Informatics | |
| A Comparison of Rule-Based and Deep Learning Models for Patient Phenotyping | 2017 | ||
| A Shared Task Involving Multi-Label Classification of Clinical Free Text | 2007 | ||
| Condensed Memory Networks for Clinical Diagnostic Inferencing | 2017 | ||
| Deep Learning for Healthcare Decision Making with EMRs | 2014 | ||
| Deep Recurrent Neural Networks for Predicting Intraoperative and Postoperative Outcomes and Trends | 2017 | ||
| Distill Knowledge from Deep Networks with Application to Healthcare Domain | 2015 | Zhengping Che/Yan Liu@University of Southern California | |
| Estimating Patient’s Health State Using Latent Structure Inferred from Clinical Time Series and Text | 2017 | ||
| Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding | 2017 | Zhengping Che/Yan Liu@University of Southern California | |
| GRAM－ Graph-Based Attention Model for Healthcare Representation Learning | 2017 | KDD | Edward Choi/Jimeng Sun |
| GIT | |||
| Impact of Data Fragmentation across healthcare centers on the accuracy of a high-throughput clinical phenotyping algorithm for specifying subjects With Type 2 Diabetes Mellitus | 2012 | JAMIA | |
| Learning to Diagnose with LSTM Recurrent Neural Networks | 2016 | ICLR | Zachary C. Lipton/David C. Kale@UCSD |
| PheKB- a Catalog and Workflow for Creating Electronic Phenotype Algorithms for Transportability | Year | Journal | Team |
| Predicting Clinical Events by Combining Static and Dynamic Information using Recurrent Neural Networks | 2016 | ||
| Recurrent Neural Networks for Multivariate Time Series with Missing Values | 2016 | ||
| Relational Machine Learning for Electronic Health Record-Driven Phenotyping | 2014 | Journal of Biomedical Informatics | |
| RETAIN－ An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism | 2016 | NIPS | Edward Choi/Jimeng Sun@GIT |
| Risk Prediction with Electronic Health Records- A Deep Learning Approach | 2015 | ||
| Structured Prediction Models for RNN based Sequence Labeling in Clinical Text | 2016 | EMNLP | |
| Temporal Pattern and Association Discovery of Diagnosis Codes Using Deep Learning | 2015 | ||
| Validation of Electronic Medical Record-Based Phenotyping Algorithm- Results and Lessons Learned from the eMERGE Network | 2013 | JAMIA |
| Title | Year | Journal | Team |
|---|---|---|---|
| A Study of Active Learning Methods for Named Entity Recognition in Clinical Text | 2015 | Journal of Biomedical Informatics | YuKun Chen/Hua Xu@UTHealth |
| A Study of Neural Word Embedding for Named Entity Recognition in Clinical Text | 2015 | Yonghui Wu/Hua Xu@UTHealth | |
| Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network | 2015 | IMIA | Yonghui Wu/Hua Xu@UTHealth |
| Unsupervised Biomedical Named Entity Recognition- Experiments with Clinical and Biological Texts | 2013 | Journal of Biomedical Informatics | Journal of Biomedical Informatics |
| Automatic Extraction of Relations Between Medical Concepts in Clinical Texts | 2011 | JAMIA | |
| Detecting Concept Relations in Clinical Text- Insights from a State-of-the-Art Model | 2013 | Journal of Biomedical Informatics | |
| Extraction of Medical Term Relations from Text | 2008 | ||
| Medical Relation Extraction with Maniflod Models | 2014 | ACL | Chang Wang/James Fan@IBM Watson |
| Relation Extraction from Clinical Texts using Domain Invariant Convolutional Neural Network | 2016 | ACL | |
| Learning a Health Knowledge Graph from Electronic Medical Records | 2017 | Scientific Reports | NYU/MIT |
| Extracting Clinical Entities and their Assertions from Chinese Electronic Medical Records Based on Machine Learning | 2016 | ||
| Extracting Information from Textual Documents in the Electronic Health Record- A Review of Recent Research | 2008 |
| Title | Year | Journal | Team |
|---|---|---|---|
| Learning Low-Dimensional Representations of Medical Concepts | 2016 | JAMIA | Y Choi/David Sontag@NYU |
| Multi-layer Representation Learning for Medical Concepts | 2016 | KDD | Edward Choi/Jimeng Sun@GIT |
| Using Deep Learning Towards Biomedical Knowledge Discovery | 2017 |
| Title | Year | Journal | Team |
|---|---|---|---|
| Biomedical Text Mining and its Applications in Cancer Research | 2013 | Journal of Biomedical Informatics | |
| Text Mining of Cancer-Related Information- Review of Current Status and Future Directions | 2014 |
| Title | Year | Journal | Team |
|---|---|---|---|
| Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks | 2017 | Pranav Rajpurkar/Andrew Y. Ng@Stanford |
| Title | Year | Journal | Team |
|---|---|---|---|
| Interleaved TextImage Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation | 2016 | JMLR | HC Shin/RM. Summers@NIH |
| Title | Year | Journal | Team |
|---|---|---|---|
| Disease Inference from Health-Related Questions via Sparse Deep Learning | 2015 | ||
| Reliable Medical Diagnosis from Crowdsourcing- Discover Trustworthy Answers from Non-Experts | 2017 |
| Title | Year | Journal | Team |
|---|---|---|---|
| A comparison of models for predicting early hospital readmissions | 2015 | Journal of Biomedical Informatics | Joseph Futoma/Joseph Lucas@DukeU |
| Predicting 30-Day All-Cause Readmissions from Hospital Inpatient Discharge Data | 2016 | Chengliang Yang/Sanjay Ranka@FloridaU | |
| Predictive Modeling of Hospital Readmission Rates using Electronic Medical Record-Wide Machine Learning- A Case-Study using Mount Sinai Heart Failure Cohort | 2017 | Icahn School of Medicine at Mount Sinai |