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Jacob Calvert

Showing results (31-40 of 42) with videos related to

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American Journal of Infection Control|January 24, 2022
A comparative analysis of machine learning approaches to predict C. difficile infection in hospitalized patientsSaarang Panchavati, Nicole S Zelin, Anurag Garikipati, et al.
Healthcare Technology Letters|December 23, 2021
Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratificationSaarang Panchavati, Carson Lam, Nicole S Zelin, et al.
Frontiers in Neurology|February 11, 2022
Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning AlgorithmJenish Maharjan, Yasha Ektefaie, Logan Ryan, et al.
Kidney International Reports|May 20, 2021
Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury PredictionSidney Le, Angier Allen, Jacob Calvert, et al.
JMIR Formative Research|August 16, 2021
Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation StudyCarson Lam, Chak Foon Tso, Abigail Green-Saxena, et al.
BMJ Open|January 29, 2018
Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICUQingqing Mao, Melissa Jay, Jana L Hoffman, et al.
JMIR Medical Informatics|October 4, 2016
Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning ApproachThomas Desautels, Jacob Calvert, Jana Hoffman, et al.
Clinical Therapeutics|April 18, 2021
Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or CorticosteroidsCarson Lam, Anna Siefkas, Nicole S Zelin, et al.
JMIR Public Health and Surveillance|October 22, 2020
A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development StudyAngier Allen, Samson Mataraso, Anna Siefkas, et al.
Journal of Clinical Medicine|December 1, 2020
Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?-The IDENTIFY TrialHoyt Burdick, Carson Lam, Samson Mataraso, et al.
Pageof 5

Showing results (31-40 of 42) with videos related to

Sort By:
Pageof 5
American Journal of Infection Control|January 24, 2022
A comparative analysis of machine learning approaches to predict C. difficile infection in hospitalized patientsSaarang Panchavati, Nicole S Zelin, Anurag Garikipati, et al.
Healthcare Technology Letters|December 23, 2021
Retrospective validation of a machine learning clinical decision support tool for myocardial infarction risk stratificationSaarang Panchavati, Carson Lam, Nicole S Zelin, et al.
Frontiers in Neurology|February 11, 2022
Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning AlgorithmJenish Maharjan, Yasha Ektefaie, Logan Ryan, et al.
Kidney International Reports|May 20, 2021
Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury PredictionSidney Le, Angier Allen, Jacob Calvert, et al.
JMIR Formative Research|August 16, 2021
Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation StudyCarson Lam, Chak Foon Tso, Abigail Green-Saxena, et al.
BMJ Open|January 29, 2018
Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICUQingqing Mao, Melissa Jay, Jana L Hoffman, et al.
JMIR Medical Informatics|October 4, 2016
Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning ApproachThomas Desautels, Jacob Calvert, Jana Hoffman, et al.
Clinical Therapeutics|April 18, 2021
Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or CorticosteroidsCarson Lam, Anna Siefkas, Nicole S Zelin, et al.
JMIR Public Health and Surveillance|October 22, 2020
A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development StudyAngier Allen, Samson Mataraso, Anna Siefkas, et al.
Journal of Clinical Medicine|December 1, 2020
Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?-The IDENTIFY TrialHoyt Burdick, Carson Lam, Samson Mataraso, et al.
Pageof 5