Lokesh Chinthala

University of Tennessee Health Science Center

United States

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Articles (12)

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2025

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2024

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2024

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2024

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2024

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2023

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2022

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2022

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2022

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2022

Collaborators (9)

Nariman Ammar

Assistant Professor of Computer Science

Illinois State University

UNITED STATES

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Arash Shaban-Nejad

Associate Professor

University of Tennessee Health Science Center

UNITED STATES

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Ann Wu

Associate Professor

Harvard Medical School and Harvard Pilgrim Health Care Institute

UNITED STATES

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Akram Mohammed

UNITED STATES

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Ibrahim Karabayir

Assistant Professor

Wake Forest Baptist Medical Center

UNITED STATES

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Xiaolei Huang

Assistant Professor

University of Memphis

UNITED STATES

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Liam Butler

Wake Forest University

UNITED STATES

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Samie Tootooni

Faculty, Assistant Professor

Loyola University Chicago

UNITED STATES

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oguz akbilgic

Associate Professor

Wake Forest School of Medicine

UNITED STATES

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Lokesh Chinthala

Research Interests

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Articles (12)

Insights from the Biorepository and Integrative Genomics pediatric resource

<i>GSDMB/ORMDL3</i> Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma

Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs.

AI-based preeclampsia detection and prediction with electrocardiogram data.

Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy

Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study

Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram.

Digital Personal Health Coaching Platform for Promoting Human Papillomavirus Infection Vaccinations and Cancer Prevention: Knowledge Graph-Based Recommendation System

Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children With Medical Complexity Presenting With Severe Sepsis.

Predicting Parkinson’s Disease and Its Pathology via Simple Clinical Variables

Predicting Parkinson's Disease and Its Pathology via Simple Clinical Variables

Features derived from blood pressure and intracranial pressure predict elevated intracranial pressure events in critically ill children

Collaborators (9)

Nariman Ammar

Arash Shaban-Nejad

Ann Wu

Akram Mohammed

Ibrahim Karabayir

Xiaolei Huang

Liam Butler

Samie Tootooni

oguz akbilgic

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