Riccardo Miotto, PhD
Riccardo Miotto, PhD
Senior Director, Machine Learning @ Tempus AI
Потвърден имейл адрес: tempus.com - Начална страница
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
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
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
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
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
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
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), 1437-1449, 2017
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
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
Federated learning of electronic health records improves mortality prediction in patients hospitalized with COVID-19
A Vaid, SK Jaladanki, J Xu, S Teng, A Kumar, S Lee, S Somani, ...
MedRxiv, 2020
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
Deep learning and the electrocardiogram: review of the current state-of-the-art
S Somani, AJ Russak, F Richter, S Zhao, A Vaid, F Chaudhry, ...
EP Europace 23 (8), 1179-1191, 2021
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
Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale
I Landi, BS Glicksberg, HC Lee, S Cherng, G Landi, M Danieletto, ...
npj Digital Medicine 3 (96), 2020
Use of physiological data from a wearable device to identify SARS-CoV-2 infection and symptoms and predict COVID-19 diagnosis: observational study
RP Hirten, M Danieletto, L Tomalin, KH Choi, M Zweig, E Golden, S Kaur, ...
Journal of medical Internet research 23 (2), e26107, 2021
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
Mount Sinai COVID Informatics Center (MSCIC): AKI in hospitalized patients with COVID-19
L Chan, K Chaudhary, A Saha, K Chauhan, A Vaid, S Zhao, I Paranjpe, ...
J Am Soc Nephrol 32 (1), 151-160, 2021
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, ...
PACIFIC SYMPOSIUM on BIOCOMPUTING 2018: Proceedings of the Pacific Symposium …, 2018
Deep learning to predict patient future diseases from the electronic health records
R Miotto, L Li, JT Dudley
Advances in Information Retrieval: 38th European Conference on IR Research …, 2016
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