Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Ritankar Das

Showing results (51-60 of 60) with videos related to

Pageof 6
Sort By:
You have reached the last page of results.This site can display upto 60 results.
BMJ Health & Care Informatics|May 2, 2020
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitalsHoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, 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.
BMC Medical Informatics and Decision Making|October 28, 2020
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitalsHoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, 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.
Journal of Clinical Medicine|April 27, 2024
Family-Centric Applied Behavior Analysis Facilitates Improved Treatment Utilization and OutcomesRobert P Adelson, Madalina Ciobanu, Anurag Garikipati, 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.
Computers in Biology and Medicine|August 18, 2020
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trialHoyt Burdick, Carson Lam, Samson Mataraso, et al.
Health Informatics Journal|December 31, 2019
Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality predictionHamid Mohamadlou, Saarang Panchavati, Jacob Calvert, et al.
Plos One|March 17, 2021
COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patientsMark Stewart, Carla Rodriguez-Watson, Adem Albayrak, et al.
Pageof 6

Showing results (51-60 of 60) with videos related to

Sort By:
Pageof 6
You have reached the last page of results.This site can display upto 60 results.
BMJ Health & Care Informatics|May 2, 2020
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitalsHoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, 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.
BMC Medical Informatics and Decision Making|October 28, 2020
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitalsHoyt Burdick, Eduardo Pino, Denise Gabel-Comeau, 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.
Journal of Clinical Medicine|April 27, 2024
Family-Centric Applied Behavior Analysis Facilitates Improved Treatment Utilization and OutcomesRobert P Adelson, Madalina Ciobanu, Anurag Garikipati, 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.
Computers in Biology and Medicine|August 18, 2020
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trialHoyt Burdick, Carson Lam, Samson Mataraso, et al.
Health Informatics Journal|December 31, 2019
Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality predictionHamid Mohamadlou, Saarang Panchavati, Jacob Calvert, et al.
Plos One|March 17, 2021
COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patientsMark Stewart, Carla Rodriguez-Watson, Adem Albayrak, et al.
Pageof 6