Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
Authors
Keywords
-
Journal
Scientific Reports
Volume 6, Issue 1, Pages -
Publisher
Springer Nature
Online
2016-05-17
DOI
10.1038/srep26094
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Prediction and Informative Risk Factor Selection of Bone Diseases
- (2015) Hui Li et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
- (2015) Junshui Ma et al. Journal of Chemical Information and Modeling
- Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials
- (2015) R. Miotto et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis
- (2015) Adler Perotte et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
- (2015) Babak Alipanahi et al. NATURE BIOTECHNOLOGY
- Machine learning: Trends, perspectives, and prospects
- (2015) M. I. Jordan et al. SCIENCE
- Identification of type 2 diabetes subgroups through topological analysis of patient similarity
- (2015) Li Li et al. Science Translational Medicine
- Predictability Bounds of Electronic Health Records
- (2015) Dominik Dahlem et al. Scientific Reports
- Deep learning of the tissue-regulated splicing code
- (2014) Michael K. K. Leung et al. BIOINFORMATICS
- Toward personalizing treatment for depression: predicting diagnosis and severity
- (2014) Sandy H Huang et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- The human splicing code reveals new insights into the genetic determinants of disease
- (2014) H. Y. Xiong et al. SCIENCE
- Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies
- (2013) Raphael Cohen et al. BMC BIOINFORMATICS
- A method for inferring medical diagnoses from patient similarities
- (2013) Assaf Gottlieb et al. BMC Medicine
- Representation Learning: A Review and New Perspectives
- (2013) Y. Bengio et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Defining and measuring completeness of electronic health records for secondary use
- (2013) Nicole G. Weiskopf et al. JOURNAL OF BIOMEDICAL INFORMATICS
- Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records
- (2013) Svetlana Lyalina et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Diagnosis code assignment: models and evaluation metrics
- (2013) Adler Perotte et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Connectomic reconstruction of the inner plexiform layer in the mouse retina
- (2013) Moritz Helmstaedter et al. NATURE
- Comorbidity Clusters in Autism Spectrum Disorders: An Electronic Health Record Time-Series Analysis
- (2013) Finale Doshi-Velez et al. PEDIATRICS
- Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data
- (2013) Thomas A. Lasko et al. PLoS One
- Probabilistic topic models
- (2012) David M. Blei COMMUNICATIONS OF THE ACM
- Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research
- (2012) N. G. Weiskopf et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Improved Cardiovascular Risk Prediction Using Nonparametric Regression and Electronic Health Record Data
- (2012) Edward H. Kennedy et al. MEDICAL CARE
- Mining electronic health records: towards better research applications and clinical care
- (2012) Peter B. Jensen et al. NATURE REVIEWS GENETICS
- Data-Driven Prediction of Drug Effects and Interactions
- (2012) N. P. Tatonetti et al. Science Translational Medicine
- Mining FDA drug labels using an unsupervised learning technique - topic modeling
- (2011) Halil Bisgin et al. BMC BIOINFORMATICS
- Electronic health records: Implications for drug discovery
- (2011) Lixia Yao et al. DRUG DISCOVERY TODAY
- The National Center for Biomedical Ontology
- (2011) Mark A Musen et al. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
- Prediction Modeling Using EHR Data
- (2010) Jionglin Wu et al. MEDICAL CARE
- Comparison of concept recognizers for building the Open Biomedical Annotator
- (2009) Nigam H Shah et al. BMC BIOINFORMATICS
- Predictive data mining in clinical medicine: Current issues and guidelines
- (2007) R BELLAZZI et al. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started