Rishikesan Kamaleswaran

University of North Carolina at Chapel Hill

Also affiliated with Duke University, Duke Medical Center

MedicineComputer Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 1%percentile

6.6Author DataRank

Indexed papers

1in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative

JAMA Network Open(2021)10.1001/jamanetworkopen.2021.16901

Top 3%

6.6DataRank

Top 3%250 citations

Richard A. Moffitt, Janos Hajagos, Benjamin Amor, Adit Anand, Mark M. Bissell +95 more

Papers

Driven by 62 papers — median percentile 97. Top paper: “Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative”.

Clinical Characterization and Prediction of Clinical Severity of SARS-CoV-2 Infection Among US Adults Using Data From the US National COVID Cohort Collaborative

JAMA Network Open(2021)10.1001/jamanetworkopen.2021.16901

Top 3%

6.6DataRank

Top 3%250 citations

Richard A. Moffitt, Janos Hajagos, Benjamin Amor, Adit Anand, Mark M. Bissell +95 more

Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission

Frontiers in Immunology(2021)10.3389/fimmu.2021.592303

N/A

0DataRank · unranked

69 citations

Akram Mohammed, Hector R. Wong, Nades Palaniyar, Rishikesan Kamaleswaran, Shayantan Banerjee

eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19

PLoS ONE(2021)10.1371/journal.pone.0257056

N/A

0DataRank · unranked

51 citations

Yash Garg, Philip Yang, Azade Tabaie, An-Kwok Ian Wong, Akram Mohammed +11 more

Cluster analysis and profiling of airway fluid metabolites in pediatric acute hypoxemic respiratory failure

Scientific Reports(2021)10.1038/s41598-021-02354-4

N/A

0DataRank · unranked

16 citations

Milad Ghiasi Rad, Susan T. Stephenson, Ahmad F. Mohammad, Cydney Opolka, Anne M. Fitzpatrick +2 more

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection

IEEE/ACM Transactions on Computational Biology and Bioinformatics(2021)10.1109/tcbb.2021.3122405

N/A

0DataRank · unranked

11 citations

Raheem Beyah, Rishikesan Kamaleswaran, Anni Zhou

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

PLOS Digital Health(2022)10.1371/journal.pdig.0000006

N/A

0DataRank · unranked

55 citations

Patrick Tighe, Tezcan Ozrazgat‐Baslanti, John P. Davis, Matthew M. Ruppert, Yuanfang Ren +8 more

Machine Learning Approaches to Identify Discriminative Signatures of Volatile Organic Compounds (VOCs) from Bacteria and Fungi Using SPME-DART-MS

Metabolites(2022)10.3390/metabo12030232

N/A

0DataRank · unranked

29 citations

Stephen Zambrzycki, Joshua M. Levy, Annette Esper, Jennifer K. Frediani, Cassandra L. Quave +3 more

A Wearable Multimodal Sensing System for Tracking Changes in Pulmonary Fluid Status, Lung Sounds, and Respiratory Markers

Sensors(2022)10.3390/s22031130

N/A

0DataRank · unranked

39 citations

John A. Berkebile, Brandi N. Nevius, Göktuğ C. Özmen, Christopher J. Nichols, Venu G. Ganti +6 more

Exacerbation-prone pediatric asthma is associated with arginine, lysine, and methionine pathway alterations

Journal of Allergy and Clinical Immunology(2022)10.1016/j.jaci.2022.07.027

N/A

0DataRank · unranked

20 citations

Susan T. Stephenson, Ahmad F. Mohammad, Susan O. Kim, Nael A. McCarty, Rishikesan Kamaleswaran +3 more

Neurocritical Care Performance Measures Derived from Electronic Health Record Data are Feasible and Reveal Site-Specific Variation: A CHoRUS Pilot Project

Neurocritical Care(2022)10.1007/s12028-022-01497-0

N/A

0DataRank · unranked

7 citations

Shamelia Y. Loiseau, Guneeti Sharma, Joshua N. Goldstein, India A. Lissak, Sarah Duffy +10 more

Functional immunophenotyping of children with critical status asthmaticus identifies differential gene expression responses in neutrophils exposed to a poly(I:C) stimulus

Scientific Reports(2022)10.1038/s41598-022-24261-y

N/A

0DataRank · unranked

4 citations

Milad Ghiasi Rad, Susan T. Stephenson, Ahmad F. Mohammad, Cydney Opolka, Anne M. Fitzpatrick +2 more

Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients

Research Square(2022)10.21203/rs.3.rs-1745568/v1

N/A

0DataRank · unranked

7 citations

Hayoung Jeong, Mengyun Yu, Xianyan Chen, Brian Murray, Rishikesan Kamaleswaran +1 more

Commentary: ‘Critical illness subclasses: all roads lead to Rome’

Critical Care(2022)10.1186/s13054-022-04265-w

N/A

0DataRank · unranked

6 citations

L. Nelson Sanchez‐Pinto, Rishikesan Kamaleswaran, Mihir R. Atreya

Initial Validation of Multi-Frequency Patch-Based Impedance Pneumography in Hospital Settings

2022 IEEE Sensors(2022)10.1109/sensors52175.2022.9967287

N/A

0DataRank · unranked

4 citations

Samer Mabrouk, John A. Berkebile, Annette Esper, Philip Yang, Rishikesan Kamaleswaran +2 more

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

Pediatric Critical Care Medicine(2023)10.1097/pcc.0000000000003425

N/A

0DataRank · unranked

28 citations

Sarah Walker, Andrea J. Fawcett, Tellen D. Bennett, Adam Dziorny, L. Nelson Sanchez‐Pinto +20 more

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU

Scientific Reports(2023)10.1038/s41598-023-46735-3

N/A

0DataRank · unranked

27 citations

Tianyi Zhang, David J. Murphy, Susan Smith, Brian Murray, Rishikesan Kamaleswaran +5 more

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

EBioMedicine(2023)10.1016/j.ebiom.2023.104938

N/A

0DataRank · unranked

23 citations

Shayantan Banerjee, Andrew J. Lautz, Matthew N. Alder, Brian M. Varisco, Hector R. Wong +20 more

Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model

Critical Care(2023)10.1186/s13054-023-04437-2

N/A

0DataRank · unranked

18 citations

Alireza Rafiei, Milad Ghiasi Rad, Kelli Keats, Susan Smith, John W. Devlin +5 more

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

Computers in Biology and Medicine(2023)10.1016/j.compbiomed.2023.107749

N/A

0DataRank · unranked

18 citations

Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran, Alireza Rafiei

Metabolomics identifies disturbances in arginine, phenylalanine, and glycine metabolism as differentiating features of exacerbating atopic asthma in children

Journal of Allergy and Clinical Immunology Global(2023)10.1016/j.jacig.2023.100115

N/A

0DataRank · unranked

14 citations

Joshua D. Chandler, Seibi Kobara, Susan T. Stephenson, Ahmad F. Mohammad, Mallory Tidwell +7 more

Identification of a pediatric acute hypoxemic respiratory failure signature in peripheral blood leukocytes at 24 hours post-ICU admission with machine learning

Frontiers in Pediatrics(2023)10.3389/fped.2023.1159473

N/A

0DataRank · unranked

5 citations

Milad Ghiasi Rad, Michael J. Ripple, Nadir Yehya, Hector R. Wong, Rishikesan Kamaleswaran +1 more

Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients

Scientific Reports(2023)10.1038/s41598-023-42657-2

N/A

0DataRank · unranked

10 citations

Hayoung Jeong, Mengyun Yu, Xianyan Chen, Brian Murray, Rishikesan Kamaleswaran +1 more

A machine learning model for predicting congenital heart defects from administrative data

Birth Defects Research(2023)10.1002/bdr2.2245

N/A

0DataRank · unranked

9 citations

Wendy Book, Cheryl Raskind‐Hood, Karrie F. Downing, Sherry L. Farr, Mary N. Bell +4 more

Functional immunophenotyping of blood neutrophils identifies novel endotypes of viral response in preschool children with recurrent wheezing

Journal of Allergy and Clinical Immunology(2023)10.1016/j.jaci.2023.08.010

N/A

0DataRank · unranked

11 citations

Ahmad F. Mohammad, Min Huang, Susan T. Stephenson, James Patrignani, Rishikesan Kamaleswaran +2 more

Synthetic seismocardiogram generation using a transformer-based neural network

Journal of the American Medical Informatics Association(2023)10.1093/jamia/ocad067

N/A

0DataRank · unranked

10 citations

Asim H. Gazi, Jonathan Zia, Sungtae An, David J. Lin, Omer T. Inan +2 more

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

Bioengineering(2023)10.3390/bioengineering10080946

N/A

0DataRank · unranked

9 citations

Carolyn Davis, Niraj Gowda, Dennis G. Foster, Angana Mondal, Craig M. Coopersmith +2 more

Enabling Continuous Breathing-Phase Contextualization via Wearable-Based Impedance Pneumography and Lung Sounds: A Feasibility Study

IEEE Journal of Biomedical and Health Informatics(2023)10.1109/jbhi.2023.3319381

N/A

0DataRank · unranked

6 citations

Asim H. Gazi, Samer Mabrouk, John A. Berkebile, Göktuğ C. Özmen, Rishikesan Kamaleswaran +2 more

A MACHINE LEARNING MODEL DERIVED FROM ANALYSIS OF TIME-COURSE GENE-EXPRESSION DATASETS REVEALS TEMPORALLY STABLE GENE MARKERS PREDICTIVE OF SEPSIS MORTALITY

Shock(2023)10.1097/shk.0000000000002226

N/A

0DataRank · unranked

6 citations

Mihir R. Atreya, Andre L. Holder, Rishikesan Kamaleswaran, Min Huang

566 Machine learning analysis of continuous glucose monitoring identifies greater degree of dysglycemia than previously suggested byoral glucose tolerance testing

Journal of Cystic Fibrosis(2023)10.1016/s1569-1993(23)01488-1

N/A

0DataRank · unranked

3 citations

T. Daley, Jessica A. Alvarez, Ryan A. Harris, J. McNeany, Yu Wang +3 more

Cluster analysis of plasma cytokines identifies two unique endotypes of children with asthma in the pediatric intensive care unit

Scientific Reports(2023)10.1038/s41598-023-30679-9

N/A

0DataRank · unranked

5 citations

Milad Ghiasi Rad, Michael J. Ripple, Susan T. Stephenson, Ahmad F. Mohammad, Mallory Tidwell +4 more

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports

BMC Medical Informatics and Decision Making(2023)10.1186/s12911-023-02369-z

N/A

0DataRank · unranked

4 citations

Joao Souza de Vale, Saransh Gupta, Pulakesh Upadhyaya, Felipe Lisboa, Seth Schobel +5 more

RNA Sequencing Analysis of CD4+ T Cells Exposed to Airway Fluid From Children With Pediatric Acute Respiratory Distress Syndrome

Critical Care Explorations(2023)10.1097/cce.0000000000000935

N/A

0DataRank · unranked

1 citations

Min Huang, Susan T. Stephenson, Ahmad F. Mohammad, Mallory Tidwell, Anne M. Fitzpatrick +3 more

Improving irregular temporal modeling by integrating synthetic data to the electronic medical record using conditional GANs: a case study of fluid overload prediction in the intensive care unit

medRxiv(2023)10.1101/2023.06.20.23291680

N/A

0DataRank · unranked

8 citations

Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran, Alireza Rafiei

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU

medRxiv(2023)10.1101/2023.06.16.23291493

N/A

0DataRank · unranked

5 citations

Tianyi Zhang, David J. Murphy, Susan Smith, Brian Murray, Rishikesan Kamaleswaran +5 more

Lung Grounded-SAM (LuGSAM): A Novel Framework for Integrating Text prompts to Segment Anything Model (SAM) for Segmentation Tasks of ICU Chest X-Rays

Figshare(2023)10.36227/techrxiv.24224761.v1

N/A

0DataRank · unranked

4 citations

R. Sridhar, Pulakesh Upadhyaya, Rishikesan Kamaleswaran, Dhanush Babu Ramesh

A Common Data Model for the standardization of intensive care unit (ICU) medication features in artificial intelligence (AI) applications

medRxiv(2023)10.1101/2023.09.18.23295727

N/A

0DataRank · unranked

2 citations

Kelli Keats, David J. Murphy, John W. Devlin, Susan Smith, Brian Murray +5 more

Lung Grounded-SAM (LuGSAM): A Novel Framework for Integrating Text prompts to Segment Anything Model (SAM) for Segmentation Tasks of ICU Chest X-Rays

(2023)10.36227/techrxiv.24224761

N/A

0DataRank · unranked

1 citations

R. Sridhar, Pulakesh Upadhyaya, Rishikesan Kamaleswaran, Dhanush Babu Ramesh

POSTCARDS from a SIESTA: Crossing the Translational and Generalizability Gap for Predictive Models of Acute Respiratory Distress Syndrome-Related Mortality*

Revue du marche commun et de l'Union Européenne(2023)10.1097/ccm.0000000000006061

N/A

0DataRank · unranked

0 citations

Rishikesan Kamaleswaran, An-Kwok Ian Wong

Derivation and validation of generalized sepsis-induced acute respiratory failure phenotypes among critically ill patients: a retrospective study

Critical Care(2024)10.1186/s13054-024-05061-4

N/A

0DataRank · unranked

14 citations

Pulakesh Upadhyaya, Carolyn Davis, Philip Yang, Simon Tallowin, Felipe Lisboa +7 more

Identification and transcriptomic assessment of latent profile pediatric septic shock phenotypes

Critical Care(2024)10.1186/s13054-024-05020-z

N/A

0DataRank · unranked

14 citations

Min Huang, A. R. Moore, Hong Zheng, Yehudit Hasin-Brumshtein, Julie C. Fitzgerald +24 more

A common data model for the standardization of intensive care unit medication features

JAMIA Open(2024)10.1093/jamiaopen/ooae033

N/A

0DataRank · unranked

10 citations

Kelli Keats, David J. Murphy, John W. Devlin, Susan Smith, Brian Murray +5 more

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

IEEE Journal of Biomedical and Health Informatics(2024)10.1109/jbhi.2024.3502575

N/A

0DataRank · unranked

9 citations

Curtis Marshall, Carolyn Davis, Philip Yang, Rishikesan Kamaleswaran, Ashwin Pathak

Parsimonious waveform-derived features consisting of pulse arrival time and heart rate variability predicts the onset of septic shock

Biomedical Signal Processing and Control(2024)10.1016/j.bspc.2024.105974

N/A

0DataRank · unranked

8 citations

Curtis Marshall, Jacob Kimball, Tilendra Choudhary, Gilles Clermont, Michael R. Pinsky +5 more

PROGNOSTIC ACCURACY OF MACHINE LEARNING MODELS FOR IN-HOSPITAL MORTALITY AMONG CHILDREN WITH PHOENIX SEPSIS ADMITTED TO THE PEDIATRIC INTENSIVE CARE UNIT

Shock(2024)10.1097/shk.0000000000002501

N/A

0DataRank · unranked

8 citations

Daniela Chanci, Stephanie Brown, Michael J. Ripple, Natalie R. Bishop, Jocelyn R. Grunwell +2 more

Robust Meta-Model for Predicting the Likelihood of Receiving Blood Transfusion in Non-traumatic Intensive Care Unit Patients

Health Data Science(2024)10.34133/hds.0197

N/A

0DataRank · unranked

7 citations

Ronald Moore, Tilendra Choudhary, Curtis Marshall, Geoffrey Smith, John D. Roback +4 more

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

Computers in Biology and Medicine(2024)10.1016/j.compbiomed.2024.109255

N/A

0DataRank · unranked

7 citations

J. McNeany, Yifei Wang, Tanicia Daley, Arlene A. Stecenko, Rishikesan Kamaleswaran +1 more

Dysfunctional neutrophil type 1 interferon responses in preschool children with recurrent wheezing and IL-4–mediated aeroallergen sensitization

Journal of Allergy and Clinical Immunology Global(2024)10.1016/j.jacig.2024.100229

N/A

0DataRank · unranked

7 citations

Min Huang, Ahmad F. Mohammad, Susan T. Stephenson, Rishikesan Kamaleswaran, Jocelyn R. Grunwell +1 more

Lung segment anything model (LuSAM): a decoupled prompt-integrated framework for automated lung segmentation on chest x-Ray images

Biomedical Physics & Engineering Express(2024)10.1088/2057-1976/ad4f8f

N/A

0DataRank · unranked

6 citations

Rishikesan Kamaleswaran, R. Sridhar

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

Journal of Critical Care(2024)10.1016/j.jcrc.2024.154833

N/A

0DataRank · unranked

1 citations

Ryohei Yamamoto, Milad Ghiasi Rad, Jocelyn R. Grunwell, Nao Hikota, Y Uzawa +4 more

Plasma metabolomics identifies differing endotypes of recurrent wheezing in preschool children differentiated by symptoms and social disadvantage

Scientific Reports(2024)10.1038/s41598-024-66878-1

N/A

0DataRank · unranked

1 citations

Jocelyn R. Grunwell, Hina Gaur, Seibi Kobara, Rishikesan Kamaleswaran, Anne M. Fitzpatrick

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

medRxiv(2024)10.1101/2024.03.21.24304663

N/A

0DataRank · unranked

4 citations

Shiyuan Deng, Xianyan Chen, Tianyi Zhang, John W. Devlin, David J. Murphy +5 more

Augmenting mortality prediction with medication data and machine learning models

medRxiv(2024)10.1101/2024.04.16.24305420

N/A

0DataRank · unranked

2 citations

Tianyi Zhang, Amoreena Most, Xianyan Chen, Susan Smith, John W. Devlin +4 more

Derivation and Validation of Generalized Sepsis-induced Acute Respiratory Failure Phenotypes Among Critically Ill Patients: A Retrospective Study

Research Square(2024)10.21203/rs.3.rs-4307475/v1

N/A

0DataRank · unranked

2 citations

Pulakesh Upadhyaya, Carolyn Davis, Philip Yang, Simon Tallowin, Felipe Lisboa +7 more

SpO 2 /FiO 2 Ratio as a Better Metric for Assessment of RBC Transfusion Effectiveness in Non-traumatic Critically Ill Patients with Physiologic Derangements

medRxiv(2024)10.1101/2024.10.03.24313829

N/A

0DataRank · unranked

0 citations

Geoffrey Smith, John D. Roback, Ravi M. Patel, Cassandra D. Josephson, Rishikesan Kamaleswaran +1 more

Transcriptomic mortality signature defines high-risk neonatal sepsis endotype

Frontiers in Immunology(2025)10.3389/fimmu.2025.1601316

N/A

0DataRank · unranked

2 citations

Min Huang, James L. Wynn, Rishikesan Kamaleswaran, Mihir R. Atreya, Faris N. Al Gharaibeh

Improving clinical decision support through interpretable machine learning and error handling in electronic health records

Journal of the American Medical Informatics Association(2025)10.1093/jamia/ocaf058

N/A

0DataRank · unranked

4 citations

Hassan Mortagy, Nathan Dwarshuis, Jeffrey Wang, Philip Yang, Andre L. Holder +3 more

A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes

Birth Defects Research(2025)10.1002/bdr2.2440

N/A

0DataRank · unranked

3 citations

Wendy M. Book, Lindsey C. Ivey, Fred H. Rodriguez, Cheryl Raskind‐Hood, Karrie F. Downing +8 more

LuGSAM: a novel framework for integrating text prompts to Segment Anything Model (SAM) for segmentation tasks of ICU chest x-rays

Multimedia Tools and Applications(2025)10.1007/s11042-025-21094-5

N/A

0DataRank · unranked

2 citations

R. Sridhar, Pulakesh Upadhyaya, Rishikesan Kamaleswaran, R Dhanush Babu

Machine learning approaches to identify neonates and young children at risk for postdischarge mortality in Dar es Salaam, Tanzania and Monrovia, Liberia

BMJ Paediatrics Open(2025)10.1136/bmjpo-2025-003547

N/A

0DataRank · unranked

3 citations

Rodrick Kisenge, Evance Godfrey, Readon C Ideh, Julia Kamara, Ye-Jeung G Coleman-Nekar +12 more

Neutrophil dysregulation differentiates pediatric septic shock biomarker-based mortality-risk strata: insights from weighted gene co-expression network and transcriptomic analyses

Frontiers in Immunology(2025)10.3389/fimmu.2025.1663704

N/A

0DataRank · unranked

2 citations

Min Huang, A. R. Moore, Natalja L. Stanski, Stephen W. Standage, Jennifer Kaplan +15 more

Evaluating the impact of common clinical confounders on performance of deep-learning-based sepsis risk assessment

Frontiers in Artificial Intelligence(2025)10.3389/frai.2025.1452471

N/A

0DataRank · unranked

0 citations

Vivek Kumar Singh, A.E. Gent, Rishikesan Kamaleswaran, Ali Kamen, Shikha Chaganti

Advancing approaches to identify young children at risk for post-discharge mortality: Protocol for a prospective observational cohort study in Western Kenya

BMJ Paediatrics Open(2025)10.1136/bmjpo-2025-004176

N/A

0DataRank · unranked

0 citations

Adrianna Westbrook, Harun Owuor, Enrico M. Novelli, Richard Omore, Robert F. Breiman +11 more

Rishikesan Kamaleswaran

Indexed papers

Top data-sharing exemplar

Papers