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Author Details
Full Name
Aditya Biswas
Affiliation
Clinical and Translational Research Accelerator, Yale University
ORCID
Career Start Year
2017
Papers
15
H Index
10
Expertise
CM4AI Collaborator
Wade Schulz (CM4AI)
PMID
Paper Title
Journal Title
Published Year
35174627
Severe inpatient hypertension prevalence and blood pressure response to antihypertensive treatment.
J Clin Hypertens (Greenwich)
2022
35385506
Blood pressure response to commonly administered antihypertensives for severe inpatient hypertension.
PLoS One
2022
35947362
Alerting Clinicians to 1-Year Mortality Risk in Patients Hospitalized With Heart Failure: The REVEAL-HF Randomized Clinical Trial.
JAMA Cardiol
2022
33422598
The Association of COVID-19 With Acute Kidney Injury Independent of Severity of Illness: A Multicenter Cohort Study.
Am J Kidney Dis
2021
35373058
Introduction to Supervised Machine Learning.
Kidney360
2021
33688965
Assessment of Acute Kidney Injury and Longitudinal Kidney Function After Hospital Discharge Among Patients With and Without COVID-19.
JAMA Netw Open
2021
33992566
REVeAL-HF: Design and Rationale of a Pragmatic Randomized Controlled Trial Embedded Within Routine Clinical Practice.
JACC Heart Fail
2021
33979353
Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study.
PLoS One
2021
33461986
Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial.
BMJ
2021
32381598
A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children.
J Am Soc Nephrol
2020
33300016
Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study.
medRxiv
2020
31154298
Electronic Alerts for Acute Kidney Injury Amelioration (ELAIA-1): a completely electronic, multicentre, randomised controlled trial: design and rationale.
BMJ Open
2019
31306408
A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study.
PLoS Med
2019
29599299
Identification of Patients Expected to Benefit from Electronic Alerts for Acute Kidney Injury.
Clin J Am Soc Nephrol
2018
28122032
Approaches to Predicting Outcomes in Patients with Acute Kidney Injury.
PLoS One
2017
1 - 15 of 15
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Michael Matheny
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row(s) 1 - 30 of 30
Collaborators
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7
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Yale University School of Medicine
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6
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Yale School of Medicine
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6
Jason H Greenberg
Yale University School of Medicine
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6
Sherry G Mansour
Yale School of Medicine
Co-authored papers
6
Chirag R Parikh
Johns Hopkins University School of Medicine
Co-authored papers
4
Jeffrey M Testani
Yale University School of Medicine
Co-authored papers
4
Amit X Garg
Western University
Co-authored papers
3
Aldo J Peixoto
Universidade Federal Rural do Rio de Janeiro
Co-authored papers
3
Paul M Palevsky
University of Pittsburgh School of Medicine
Co-authored papers
3
Eric J Velazquez
Yale School of Medicine
Co-authored papers
2
Allen L Hsiao
Yale University School of Medicine
Co-authored papers
2
Monique Hinchcliff
Yale School of Medicine
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