Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Riccardo Miotto"'
Autor:
Riccardo Miotto, Benjamin S. Glicksberg, Lili Chan, Allan C. Just, Felix Richter, Anuradha Lala, Valentin Fuster, Girish N. Nadkarni, Arash Kia, Carlos Cordon-Cardo, Akhil Vaid, Alexander W. Charney, Aparna Saha, Robert Freeman, Sulaiman Somani, Prem Timsina, Eric E. Schadt, Barbara Murphy, John Cijiang He, Ishan Paranjpe, David Reich, Kumardeep Chaudhary, Matthew A. Levin, Shan Zhao, Jagat Narula, Steven G. Coca, Rong Chen, Erwin P. Bottinger, Li Li, Kinsuk Chauhan, Carol R. Horowitz, Zahi A. Fayad
Publikováno v:
Journal of the American Society of Nephrology. 32:151-160
Background Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. Method
Autor:
Sarah T. Cherng, Riccardo Miotto, Benjamin S. Glicksberg, Cesare Furlanello, Hao-Chih Lee, Matteo Danieletto, Giulia Landi, Isotta Landi, Joel T. Dudley
Publikováno v:
npj Digital Medicine, Vol 3, Iss 1, Pp 1-11 (2020)
NPJ Digital Medicine
NPJ Digital Medicine
Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysi
Autor:
Riccardo Miotto, Fayzan Chaudhry, Adam Russak, Shan Zhao, Benjamin S. Glicksberg, Tejeshwar Bawa, Kipp W. Johnson, Phillip D. Levy, Mohsin Ali, Jessica K De Freitas, Solomon Bienstock, Akhil Vaid, Felix Richter, Sulaiman Somani, Farhan Chaudhry, Garrett Baron, Girish N. Nadkarni, Ishan Paranjpe
Publikováno v:
Journal of Cardiovascular Pharmacology and Therapeutics. 25:379-390
Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage,
Autor:
Jessica K De Freitas, Girish N. Nadkarni, Joel T. Dudley, Riccardo Miotto, Kipp W. Johnson, Eddye Golden, Benjamin S. Glicksberg, Erwin P. Bottinger
Publikováno v:
Patterns
Summary Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and asse
Autor:
Ariful Azad, Benjamin S. Glicksberg, Ying Ding, Jessica K De Freitas, Akhil Vaid, Sulaiman Somani, Tingyi Wanyan, Riccardo Miotto, Girish N. Nadkarni
Publikováno v:
IEEE transactions on big data
Traditional Machine Learning (ML) models have had limited success in predicting Coronoavirus-19 (COVID-19) outcomes using Electronic Health Record (EHR) data partially due to not effectively capturing the inter-connectivity patterns between various d
Publikováno v:
npj Digital Medicine, Vol 1, Iss 1, Pp 1-7 (2018)
NPJ Digital Medicine
NPJ Digital Medicine
Inexpensive embedded computing and the related Internet of Things technologies enable the recent development of smart products that can respond to human needs and improve everyday tasks in an attempt to make traditional environments more “intellige
Publikováno v:
Jamia Open
ObjectivesTraditionally, summarization of research themes and trends within a given discipline was accomplished by manual review of scientific works in the field. However, with the ushering in of the age of “big data,” new methods for discovery o
Autor:
Katie Hyewon Choi, Drew Helmus, Renata Pyzik, Sparshdeep Kaur, Erwin P. Bottinger, Micol Zweig, Benjamin S. Glicksberg, Riccardo Miotto, Ismail Nabeel, Dennis S. Charney, Anthony Biello, Laurie Keefer, Mayte Suárez-Fariñas, David Reich, Eddye Golden, Zahi A. Fayad, Matteo Danieletto, Lewis Tomalin, Girish N. Nadkarni, Judith A. Aberg, Matthew A. Levin, Robert Hirten, Alexander W. Charney
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 2, p e26107 (2021)
Journal of Medical Internet Research
Journal of Medical Internet Research
Background Changes in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. Objective We performed an evaluation of HRV collected by a
Autor:
Matthew A. Levin, Arash Kia, Adam Russak, Paul F. O'Reilly, Jeffrey S. Jhang, Allan C. Just, Judith A. Aberg, Jessica K De Freitas, Zahi A. Fayad, Suraj K Jaladanki, Emilia Bagiella, Manbir Singh, Udit Nangia, V Fuster, Robert Freeman, Benjamin S. Glicksberg, Anuradha Lala, Carlos Cordon-Cardo, Prem Timsina, Erwin P. Bottinger, Dennis S. Charney, Kipp W. Johnson, Eddye Golden, Matteo Danieletto, Ishan Paranjpe, David Reich, Joseph Finkelstein, Riccardo Miotto, Alexander W. Charney, Patricia Kovatch, Sayan Manna, Laura M. Huckins, Barbara Murphy, Girish N. Nadkarni, Patricia Glowe, Eric J. Nestler, Carol R. Horowitz, Jagat Narula, Arjun Kapoor, Akhil Vaid, Dara Meyer, Sulaiman Somani, Ross O'Hagan, Adolfo Firpo
Publikováno v:
BMJ Open, Vol 10, Iss 11 (2020)
BMJ Open
BMJ Open
ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical ch
Autor:
Riccardo Miotto, Samuel J. Lee, Ishan Paranjpe, Fei Wang, Arvind Kumar, Zahi A. Fayad, Jessica K De Freitas, Jie Xu, Shelly Teng, Young Joon Kwon, Mesude Bicak, Tingyi Wanyan, Kipp W. Johnson, Benjamin S. Glicksberg, Shan Zhao, Girish N. Nadkarni, Eyal Klang, Akhil Vaid, Erwin P. Bottinger, Suraj K. Jaladanki, Sulaiman Somani, Anthony Costa, Alexander W. Charney
Publikováno v:
medRxiv
article-version (status) pre
article-version (number) 1
JMIR Medical Informatics
JMIR Medical Informatics, Vol 9, Iss 1, p e24207 (2021)
article-version (status) pre
article-version (number) 1
JMIR Medical Informatics
JMIR Medical Informatics, Vol 9, Iss 1, p e24207 (2021)
Background Machine learning models require large datasets that may be siloed across different health care institutions. Machine learning studies that focus on COVID-19 have been limited to single-hospital data, which limits model generalizability. Ob