Rishikesan Kamaleswaran
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Geciteerd door
The National COVID Cohort Collaborative (N3C): rationale, design, infrastructure, and deployment
MA Haendel, CG Chute, TD Bennett, DA Eichmann, J Guinney, WA Kibbe, ...
Journal of the American Medical Informatics Association 28 (3), 427-443, 2021
Clinical characterization and prediction of clinical severity of SARS-CoV-2 infection among US adults using data from the US National COVID Cohort Collaborative
TD Bennett, RA Moffitt, JG Hajagos, B Amor, A Anand, MM Bissell, ...
JAMA network open 4 (7), e2116901-e2116901, 2021
Analysis of discrepancies between pulse oximetry and arterial oxygen saturation measurements by race and ethnicity and association with organ dysfunction and mortality
AKI Wong, M Charpignon, H Kim, C Josef, AAH De Hond, JJ Fojas, ...
JAMA Network Open 4 (11), e2131674-e2131674, 2021
Applying artificial intelligence to identify physiomarkers predicting severe sepsis in the PICU
R Kamaleswaran, O Akbilgic, MA Hallman, AN West, RL Davis, SH Shah
Pediatric Critical Care Medicine 19 (10), e495-e503, 2018
A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length
R Kamaleswaran, R Mahajan, O Akbilgic
Physiological measurement 39 (3), 035006, 2018
Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER program
MD Brannock, RF Chew, AJ Preiss, EC Hadley, S Redfield, JA McMurry, ...
Nature communications 14 (1), 2914, 2023
A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier
F van Wyk, A Khojandi, A Mohammed, E Begoli, RL Davis, ...
International journal of medical informatics 122, 55-62, 2019
Autotriage-an open source edge computing raspberry pi-based clinical screening system
C Hegde, Z Jiang, PB Suresha, J Zelko, S Seyedi, MA Smith, DW Wright, ...
medrxiv, 2020.04. 09.20059840, 2020
Improving prediction performance using hierarchical analysis of real-time data: a sepsis case study
F Van Wyk, A Khojandi, R Kamaleswaran
IEEE journal of biomedical and health informatics 23 (3), 978-986, 2019
Machine learning identifies complicated sepsis course and subsequent mortality based on 20 genes in peripheral blood immune cells at 24 H post-ICU admission
S Banerjee, A Mohammed, HR Wong, N Palaniyar, R Kamaleswaran
Frontiers in immunology 12, 592303, 2021
Cardiac rhythm classification from a short single lead ECG recording via random forest
R Mahajan, R Kamaleswaran, JA Howe, O Akbilgic
2017 Computing in Cardiology (CinC), 1-4, 2017
PhysOnline: an open source machine learning pipeline for real-time analysis of streaming physiological waveform
JR Sutton, R Mahajan, O Akbilgic, R Kamaleswaran
IEEE journal of biomedical and health informatics 23 (1), 59-65, 2018
Ideal algorithms in healthcare: explainable, dynamic, precise, autonomous, fair, and reproducible
TJ Loftus, PJ Tighe, T Ozrazgat-Baslanti, JP Davis, MM Ruppert, Y Ren, ...
PLOS digital health 1 (1), e0000006, 2022
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
L Singhal, Y Garg, P Yang, A Tabaie, AI Wong, A Mohammed, L Chinthala, ...
PloS one 16 (9), e0257056, 2021
Temporal differential expression of physiomarkers predicts sepsis in critically ill adults
A Mohammed, F Van Wyk, LK Chinthala, A Khojandi, RL Davis, ...
Shock 56 (1), 58-64, 2021
How much data should we collect? A case study in sepsis detection using deep learning
F van Wyk, A Khojandi, R Kamaleswaran, O Akbilgic, S Nemati, RL Davis
2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT …, 2017
Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients
A Mohammed, Y Cui, VR Mas, R Kamaleswaran
Scientific reports 9 (1), 11270, 2019
Electrocardiographic changes predate Parkinson’s disease onset
O Akbilgic, R Kamaleswaran, A Mohammed, GW Ross, K Masaki, ...
Scientific reports 10 (1), 11319, 2020
A wearable multimodal sensing system for tracking changes in pulmonary fluid status, lung sounds, and respiratory markers
JA Sanchez-Perez, JA Berkebile, BN Nevius, GC Ozmen, CJ Nichols, ...
Sensors 22 (3), 1130, 2022
Machine learning methods to predict acute respiratory failure and acute respiratory distress syndrome
AKI Wong, PC Cheung, R Kamaleswaran, GS Martin, AL Holder
Frontiers in big Data 3, 579774, 2020
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Artikelen 1–20