Rishikesan Kamaleswaran

Associate Professor

Emory University

United States

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Rishikesan Kamaleswaran is an Associate Professor at Emory University in the United States. His research areas encompass critical care medicine, machine learning applications in healthcare, and personalized diabetes management. Recent publications include studies on the assessment of RBC transfusion effectiveness, in-hospital mortality related to sepsis in children, and the use of natural language processing for identifying acute respiratory distress syndrome.

Articles (15)

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2025

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2025

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2023

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2022

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2020

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2020

Collaborators (8)

John W. Devlin

UNITED STATES

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Ashley Naimi

Associate Professor

Emory University

UNITED STATES

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Samuel Jenness

Associate Professor

Emory University

UNITED STATES

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Patrick Tighe

Associate Professor

University of Florida

UNITED STATES

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Craig M. Coopersmith

Emory University School of Medicine

UNITED STATES

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Brian Murray

Assistant Professor

UNITED STATES

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Asim Gazi

Georgia Institute of Technology

UNITED STATES

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William Hogan

Professor and Director

Medical College of Wisconsin

UNITED STATES

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Rishikesan Kamaleswaran

Research Interests

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Articles (15)

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction

SpO2/FiO2 ratio as a better metric for assessment of RBC transfusion effectiveness in non-traumatic critically ill patients with physiologic derangements

Association of the child opportunity index with in-hospital mortality and persistence of organ dysfunction at one week after onset of Phoenix Sepsis among children admitted to the pediatric intensive care unit with suspected infection

Tackling the small imbalanced horizontal dataset regressions by Stability Selection and SMOGN: a case study of ventilation-free days prediction in the pediatric intensive care unit and the importance of PRISM

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS)

Riemannian manifold-based geometric clustering of continuous glucose monitoring to improve personalized diabetes management

Understanding Typology of Preexposure Prophylaxis (PrEP) Persistence Trajectories Among Male PrEP Users in the United States

Improving mixed-integer temporal modeling by generating synthetic data using conditional generative adversarial networks: A case study of fluid overload prediction in the intensive care unit

Association between comorbidities at ICU admission and post-Sepsis physical impairment: A retrospective cohort study

Augmenting mortality prediction with medication data and machine learning models

Uncertainty-Aware Convolutional Neural Network for Identifying Bilateral Opacities on Chest X-rays: A Tool to Aid Diagnosis of Acute Respiratory Distress Syndrome

Synthetic seismocardiogram generation using a transformer-based neural network

Ideal algorithms in healthcare: Explainable, dynamic, precise, autonomous, fair, and reproducible

Big data in the assessment of pediatric medication safety

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study

Collaborators (8)

John W. Devlin

Ashley Naimi

Samuel Jenness

Patrick Tighe

Craig M. Coopersmith

Brian Murray

Asim Gazi

William Hogan

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