Vitaly Herasevich

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Consultant/Professor of Anesthesiology and Medicine

Mayo Clinic

United States

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About

Vitaly Herasevich is a Consultant and Professor of Anesthesiology and Medicine at Mayo Clinic in the United States. His research areas include the application of artificial intelligence and machine learning in healthcare, clinical decision support systems, and critical care management. He has authored numerous articles investigating topics such as diagnostic models for unusual infections and clinician activity patterns in intensive care settings.

Recent Grants

Grant: Close

4TDS: Trauma Triage, Treatment, and Training Decision Support

Open Date: 2018-10-01

Close Date: 2020-09-01

Grant: Close

Acute Care Learning Laboratory – Reducing Threats to Diagnostic Fidelity in Critical Illness.

Open Date: 2018-07-01

Close Date: 2022-06-01

Grant: Close

Implementation of the AWARE system to support virtual critical in a MEDCEN and CSH

Open Date: 2017-11-01

Close Date: 2020-10-01

Grant: Close

Patient-centric electronic environment for improving acute care performance.

Open Date: 2012-07-01

Close Date: 2015-06-01

Articles (14)

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2024

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2020

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2020

Collaborators (2)

Siddharth Dugar

Associate Professor

Cleveland Clinic Lerner Research Institute

UNITED STATES

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JAEYOUNG PARK

Assistant Professor

University of Central Florida

UNITED STATES

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Vitaly Herasevich

Research Interests

Explore related searches

Contact this professor

About

Recent Grants

Articles (14)

Clinician and Visitor Activity Patterns in an Intensive Care Unit Room: A Study to Examine How Ambient Monitoring Can Inform the Measurement of Delirium Severity and Escalation of Care

Development and validation of a preliminary multivariable diagnostic model for identifying unusual infections in hospitalized patients

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Who needs clinician attention first? A qualitative study of critical care clinicians’ needs that enable the prioritization of care for populations of acutely ill patients

Effect of an Artificial Intelligence Decision Support Tool on Palliative Care Referral in Hospitalized Patients: A Randomized Clinical Trial

Time to diagnostic certainty for saddle pulmonary embolism in hospitalized patients

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review

Effects of Image Quality on the Accuracy Human Pose Estimation and Detection of Eye Lid Opening/Closing Using Openpose and DLib

A Survey of Tele-Critical Care State and Needs in 2019 and 2020 Conducted among the Members of the Society of Critical Care Medicine

Effectiveness of automated alerting system compared to usual care for the management of sepsis

A multidisciplinary approach to the development of digital twin models of critical care delivery in intensive care units

Utility of AI models in critical care: union of man and the machine

Starter Kit for Geotagging and Geovisualization in Health Care: Resource Paper

Tele-critical care: An update from the society of critical care medicine tele-ICU committee

Collaborators (2)

Siddharth Dugar

JAEYOUNG PARK

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