Rishikesan Kamaleswaran
- Department of Biomedical Informatics
Adjunct Associate Professor
-
Emory University School of Medicine
Department of Biomedical Informatics
101 Woodruff Circle, Suite 4127
Overview
Rishi Kamaleswaran, PhD, is an Associate Professor of Surgery and Anesthesiology at Duke University School of Medicine and Adjunct Faculty in Biomedical Informatics at Emory University School of Medicine. A computer scientist by training, he develops machine learning models using multimodal data to improve patient outcomes, with expertise spanning ICU physiology, omics data, and biomedical engineering. Much of his recent work involves modeling complex multimodal insight to study the mechanisms behind the onset of deterioration in critically ill and immunocompromised patients across the lifespan, such as progression to single or multiple organ dysfunction, sepsis, respiratory and neurological dysfunction. His goal for his research program is based on developing intelligent systems that can be used to develop new cures for diseases and advance clinical understanding of critical and acute illness. He has been funded by the NIH and other industry and private foundations to advance research in those fields.
Academic Appointment
- Associate Professor, Emory University School of Medicine
Education
Degrees
- Doctor of Philosophy in Computer Science (Ph.D.) from University of Ontario Institute of Technology
- Master of Science in Computer Science (MSc.) from University of Ontario Institute of Technology
- Bachelors of Health Sciences (BHSc.) from University of Ontario Institute of Technology
Research
Publications
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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.
PLOS Digit Health Volume: 4 Page(s): e0000763
04/01/2025 Authors: Moore R; Chanci D; Brown SR; Ripple MJ; Bishop NR; Grunwell J; Kamaleswaran R -
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.
Int J Med Inform Volume: 196 Page(s): 105809
04/01/2025 Authors: Rad M; Rafiei A; Grunwell J; Kamaleswaran R -
Clinicians' Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study.
J Med Internet Res Volume: 27 Page(s): e62957
03/28/2025 Authors: Song J; Sridhar RI; Rogers DM; Hiddleson C; Davis C; Holden TL; Ramsey-Haynes S; Reif L; Swann J; Jabaley CS -
NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit
Algorithm with Uncertainty Quantification for Early Sepsis Prediction
03/20/2025 Authors: Zhou A; Beyah R; Kamaleswaran R -
Sepsyn-OLCP: An Online Learning-based Framework for Early Sepsis
Prediction with Uncertainty Quantification using Conformal Prediction
03/18/2025 Authors: Zhou A; Raheem B; Kamaleswaran R; Xie Y -
PREDICTING SEPSIS-INDUCED HYPOTENSION PATIENT ATTRIBUTES FOR RESTRICTIVE VERSUS LIBERAL FLUID STRATEGY.
Shock Volume: 63 Page(s): 399 - 405
03/01/2025 Authors: Upadhyaya P; Wang J; Mathew DT; Ali A; Tallowin S; Gann E; Lisboa FA; Schobel SA; Elster EA; Buchman TG -
Development of a Core Critical Care Data Dictionary With Common Data Elements to Characterize Critical Illness and Injuries Using a Modified Delphi Method.
Crit Care Med
02/21/2025 Authors: Murphy DJ; Anderson W; Heavner SH; Al-Hakim T; Cruz-Cano R; Laudanski K; Kamaleswaran R; Badawi O; Engel H; Grunwell J -
A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.
Birth Defects Res Volume: 117 Page(s): e2440
02/01/2025 Authors: Shi H; Book WM; Ivey LC; Rodriguez FH; Raskind-Hood C; Downing KF; Farr SL; McCracken CE; Leedom VO; Haynes SE -
Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.
Pharmacotherapy Volume: 45 Page(s): 76 - 86
02/01/2025 Authors: Henry K; Deng S; Chen X; Zhang T; Devlin JW; Murphy DJ; Smith SE; Murray B; Kamaleswaran R; Most A -
RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).
IEEE J Biomed Health Inform Volume: 29 Page(s): 1455 - 1463
02/01/2025 Authors: Pathak A; Marshall C; Davis C; Yang P; Kamaleswaran R