|Deep patient: an unsupervised representation to predict the future of patients from the electronic health records|
R Miotto, L Li, BA Kidd, JT Dudley
Scientific reports 6 (1), 1-10, 2016
|Deep learning for healthcare: review, opportunities and challenges|
R Miotto, F Wang, S Wang, X Jiang, JT Dudley
Briefings in bioinformatics 19 (6), 1236-1246, 2018
|Artificial intelligence in cardiology|
KW Johnson, J Torres Soto, BS Glicksberg, K Shameer, R Miotto, M Ali, ...
Journal of the American College of Cardiology 71 (23), 2668-2679, 2018
|Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams|
K Shameer, MA Badgeley, R Miotto, BS Glicksberg, JW Morgan, ...
Briefings in bioinformatics 18 (1), 105-124, 2017
|A functional genomics predictive network model identifies regulators of inflammatory bowel disease|
LA Peters, J Perrigoue, A Mortha, A Iuga, W Song, EM Neiman, ...
Nature genetics 49 (10), 1437, 2017
|AKI in hospitalized patients with COVID-19|
L Chan, K Chaudhary, A Saha, K Chauhan, A Vaid, S Zhao, I Paranjpe, ...
Journal of the American Society of Nephrology 32 (1), 151-160, 2021
|Predictive modeling of hospital readmission rates using electronic medical record-wide machine learning: a case-study using Mount Sinai heart failure cohort|
K Shameer, KW Johnson, A Yahi, R Miotto, LI Li, D Ricks, J Jebakaran, ...
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017, 276-287, 2017
|Coronavirus 2019 and people living with human immunodeficiency virus: outcomes for hospitalized patients in New York City|
K Sigel, T Swartz, E Golden, I Paranjpe, S Somani, F Richter, ...
Clinical Infectious Diseases 71 (11), 2933-2938, 2020
|Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trials|
R Miotto, C Weng
Journal of the American Medical Informatics Association 22 (e1), e141-e150, 2015
|Natural language processing of clinical notes on chronic diseases: systematic review|
S Sheikhalishahi, R Miotto, JT Dudley, A Lavelli, F Rinaldi, V Osmani
JMIR medical informatics 7 (2), e12239, 2019
|Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City|
I Paranjpe, AJ Russak, JK De Freitas, A Lala, R Miotto, A Vaid, ...
BMJ open 10 (11), e040736, 2020
|A generative context model for semantic music annotation and retrieval|
R Miotto, G Lanckriet
IEEE Transactions on Audio, Speech, and Language Processing 20 (4), 1096-1108, 2011
|Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning|
K Shameer, BS Glicksberg, R Hodos, KW Johnson, MA Badgeley, ...
Briefings in bioinformatics 19 (4), 656-678, 2018
|Automated disease cohort selection using word embeddings from Electronic Health Records.|
BS Glicksberg, R Miotto, KW Johnson, K Shameer, L Li, R Chen, ...
PSB, 145-156, 2018
|A Music Identification System Based on Chroma Indexing and Statistical Modeling.|
R Miotto, N Orio
ISMIR, 301-306, 2008
|A human–computer collaborative approach to identifying common data elements in clinical trial eligibility criteria|
Z Luo, R Miotto, C Weng
Journal of biomedical informatics 46 (1), 33-39, 2013
|Deep learning to predict patient future diseases from the electronic health records|
R Miotto, L Li, JT Dudley
European Conference on Information Retrieval, 768-774, 2016
|Improving Auto-tagging by Modeling Semantic Co-occurrences.|
R Miotto, L Barrington, GRG Lanckriet
ISMIR, 297-302, 2010
|Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation|
A Vaid, S Somani, AJ Russak, JK De Freitas, FF Chaudhry, I Paranjpe, ...
Journal of medical Internet research 22 (11), e24018, 2020
|Unsupervised mining of frequent tags for clinical eligibility text indexing|
R Miotto, C Weng
Journal of biomedical informatics 46 (6), 1145-1151, 2013