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BMJ Open Quality
|
February 17, 2018
Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units
Andrea McCoy, Ritankar Das
Royal Society Open Science
|
August 10, 2017
Machine learning landscapes and predictions for patient outcomes
Ritankar Das, David J Wales
Physical Review. E
|
July 15, 2016
Energy landscapes for a machine-learning prediction of patient discharge
Ritankar Das, David J Wales
Diagnostics (Basel, Switzerland)
|
February 21, 2019
Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients
Jacob Calvert, Nicholas Saber, Jana Hoffman, et al.
The Journal of Chemical Physics
|
April 3, 2016
Energy landscapes for a machine learning application to series data
Andrew J Ballard, Jacob D Stevenson, Ritankar Das, et al.
Journal of Biosciences
|
December 14, 2018
Computational neuroscience and neuroinformatics: Recent progress and resources
Losiana Nayak, Abhijit Dasgupta, Ritankar Das, et al.
JMIR Public Health and Surveillance
|
May 17, 2021
Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study
Chak Foon Tso, Anurag Garikipati, Abigail Green-Saxena, et al.
American Journal of Infection Control
|
August 24, 2021
Early prediction of central line associated bloodstream infection using machine learning
Keyvan Rahmani, Anurag Garikipati, Gina Barnes, et al.
Pancreatology : Official Journal of the International Association of Pancreatology (IAP) ... [Et Al.]
|
October 25, 2021
Early prediction of severe acute pancreatitis using machine learning
Rahul Thapa, Zohora Iqbal, Anurag Garikipati, et al.
BMJ Open Respiratory Research
|
February 14, 2018
Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial
David W Shimabukuro, Christopher W Barton, Mitchell D Feldman, et al.
Page
of 6
Search research articles
Search
Showing results (1-10 of 60) with videos related to
Sort By:
Page
of 6
BMJ Open Quality
|
February 17, 2018
Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units
Andrea McCoy, Ritankar Das
Royal Society Open Science
|
August 10, 2017
Machine learning landscapes and predictions for patient outcomes
Ritankar Das, David J Wales
Physical Review. E
|
July 15, 2016
Energy landscapes for a machine-learning prediction of patient discharge
Ritankar Das, David J Wales
Diagnostics (Basel, Switzerland)
|
February 21, 2019
Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients
Jacob Calvert, Nicholas Saber, Jana Hoffman, et al.
The Journal of Chemical Physics
|
April 3, 2016
Energy landscapes for a machine learning application to series data
Andrew J Ballard, Jacob D Stevenson, Ritankar Das, et al.
Journal of Biosciences
|
December 14, 2018
Computational neuroscience and neuroinformatics: Recent progress and resources
Losiana Nayak, Abhijit Dasgupta, Ritankar Das, et al.
JMIR Public Health and Surveillance
|
May 17, 2021
Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study
Chak Foon Tso, Anurag Garikipati, Abigail Green-Saxena, et al.
American Journal of Infection Control
|
August 24, 2021
Early prediction of central line associated bloodstream infection using machine learning
Keyvan Rahmani, Anurag Garikipati, Gina Barnes, et al.
Pancreatology : Official Journal of the International Association of Pancreatology (IAP) ... [Et Al.]
|
October 25, 2021
Early prediction of severe acute pancreatitis using machine learning
Rahul Thapa, Zohora Iqbal, Anurag Garikipati, et al.
BMJ Open Respiratory Research
|
February 14, 2018
Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial
David W Shimabukuro, Christopher W Barton, Mitchell D Feldman, et al.
Page
of 6