A framework for nursing documentation enabling integration with HER and real-time patient monitoring. - Jennifer Percival; Carolyn McGregor; Nathan Percival; Rishikesan Kamaleswaran; Sascha Tuuha (CBMS, 2010)

On the integration of an artifact system and a real-time healthcare analytics system. - Marion Blount; Carolyn McGregor; Andrew James; Daby M. Sow; Rishikesan Kamaleswaran; Sascha Tuuha; Jennifer Percival; Nathan Percival (IHI, 2010)

A method for interactive hypothesis testing for clinical decision support systems using Ptolemy II. - Rishikesan Kamaleswaran; Mike Eklund (CCECE, 2011)

A novel framework for event stream processing of clinical practice guidelines. - Rishikesan Kamaleswaran; Carolyn McGregor; Andrew James (BHI, 2012)

CBPsp: Complex Business Processes for Stream Processing. - Rishikesan Kamaleswaran; Carolyn McGregor (CCECE, 2012)

Integrating complex business processes for knowledge-driven clinical decision support systems. - Rishikesan Kamaleswaran; Carolyn McGregor (EMBC, 2012)

Cloud framework for real-time synchronous physiological streams to support rural and remote Critical Care. - Rishikesan Kamaleswaran; Anirudh Thommandram; Qi Zhou; J. Mikael Eklund; Yun Cao; W. P. Wang; Carolyn McGregor (CBMS, 2013)

A Real-Time Multi-dimensional Visualization Framework for Critical and Complex Environments. - Rishikesan Kamaleswaran; Carolyn McGregor (CBMS, 2014)

CoRAD: Visual Analytics for Cohort Analysis. - Rishikesan Kamaleswaran; Andrew James; Christopher Collins 001; Carolyn McGregor (ICHI, 2016)

PhysioEx: Visual Analysis of Physiological Event Streams. - Rishikesan Kamaleswaran; Christopher Collins 001; Andrew James; Carolyn McGregor (Comput. Graph. Forum, 2016)

Cardiac Rhythm Classification from a Short Single Lead ECG Recording via Random Forest. - Ruhi Mahajan; Rishikesan Kamaleswaran; John Andrew Howe; Oguz Akbilgic (CinC, 2017)

Effects of Varying Sampling Frequency on the Analysis of Continuous ECG Data Streams. - Ruhi Mahajan; Rishikesan Kamaleswaran; Oguz Akbilgic (DMAH@VLDB, 2017)

A hybrid feature extraction method to detect Atrial Fibrillation from single lead ECG recording. - Ruhi Mahajan; Rishikesan Kamaleswaran; Oguz Akbilgic (BHI, 2018)

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier. - Franco van Wyk; Anahita Khojandi; Akram Mohammed; Edmon Begoli; Robert L. Davis; Rishikesan Kamaleswaran (Int. J. Medical Informatics, 2019)

A Cost-Benefit Analysis of Automated Physiological Data Acquisition Systems Using Data-Driven Modeling. - Franco van Wyk; Anahita Khojandi; Brian Williams; Don Macmillan; Robert L. Davis; Daniel A. Jacobson; Rishikesan Kamaleswaran (J. Heal. Informatics Res., 2019)

Correction to: A Cost-Benefit Analysis of Automated Physiological Data Acquisition Systems Using Data-Driven Modeling. - Franco van Wyk; Anahita Khojandi; Brian Williams; Don Macmillan; Robert L. Davis; Daniel A. Jacobson; Rishikesan Kamaleswaran (J. Heal. Informatics Res., 2019)

PhysOnline: An Open Source Machine Learning Pipeline for Real-Time Analysis of Streaming Physiological Waveform. - Jacob R. Sutton; Ruhi Mahajan; Oguz Akbilgic; Rishikesan Kamaleswaran (IEEE J. Biomed. Health Informatics, 2019)

Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study. - Franco van Wyk; Anahita Khojandi; Rishikesan Kamaleswaran (IEEE J. Biomed. Health Informatics, 2019)

Predicting Volume Responsiveness Among Sepsis Patients Using Clinical Data and Continuous Physiological Waveforms. - Rishikesan Kamaleswaran; Jiaoying Lian; Dong-Lien Lin; Himasagar Molakapuri; Sri Manikanth Nunna; Parth Shah; Shiv Dua; Rema Padman (AMIA, 2020)

Machine learning predicts early onset of fever from continuous physiological data of critically ill patients. - Aditya Singh; Akram Mohammed; Lokesh K. Chinthala; Rishikesan Kamaleswaran (CoRR, 2020)

Machine Learning Methods to Predict Acute Respiratory Failure and Acute Respiratory Distress Syndrome. - An-Kwok Ian Wong; Patricia C. Cheung; Rishikesan Kamaleswaran; Greg S. Martin; Andre L. Holder (Frontiers Big Data, 2020)

Predicting Same Hospital Readmission following Fontan Cavopulmonary Anastomosis using Machine Learning. - Kushal Kodnad; Azade Tabaie; Joshua M. Rosenblum; Rishikesan Kamaleswaran (BIBM, 2021)

HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study. - Zeyu Liu 002; Anahita Khojandi; Akram Mohammed; Xueping Li; Lokesh K. Chinthala; Robert L. Davis; Rishikesan Kamaleswaran (Comput. Biol. Medicine, 2021)

Predicting presumed serious infection among hospitalized children on central venous lines with machine learning. - Azade Tabaie; Evan W. Orenstein; Shamim Nemati; Rajit K. Basu; Swaminathan Kandaswamy; Gari D. Clifford; Rishikesan Kamaleswaran (Comput. Biol. Medicine, 2021)

Inferring Granger Causality from Irregularly Sampled Time Series. - Song Wei; Yao Xie 002; Christopher S. Josef; Rishikesan Kamaleswaran (CoRR, 2021)

Challenges in Custom Machine Learning Model Implementation in a Vendor System: Use of a Deep Learning Model for Pediatric CLABSI Prediction. - Jonathan M. Beus; Edwin Ray; Sarah Thompson; Ryan Birmingham; Brad Cundiff; Mike Malto; Kevin Duncan; Dileep Gunda; Rishikesan Kamaleswaran; Evan Orenstein (AMIA, 2022)

Online Critical-State Detection of Sepsis Among ICU Patients using Jensen-Shannon Divergence. - Jeffrey Smith; Christopher S. Josef; Yao Xie 002; Rishikesan Kamaleswaran (AMIA, 2022)

Initial Validation of Multi-Frequency Patch-Based Impedance Pneumography in Hospital Settings. - Jesus Antonio Sanchez-Perez; Samer Mabrouk; John A. Berkebile; Annette Esper; Philip Yang; Rishikesan Kamaleswaran; Omer T. Inan (IEEE SENSORS, 2022)

Improving Sepsis Prediction Model Generalization With Optimal Transport. - Jie Wang 049; Ronald Moore; Yao Xie 002; Rishikesan Kamaleswaran (ML4H@NeurIPS, 2022)

UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. - Yanbo Xu; Alind Khare; Glenn Matlin; Monish Ramadoss; Rishikesan Kamaleswaran; Chao Zhang; Alexey Tumanov (NeurIPS, 2022)

ALRt: An Active Learning Framework for Irregularly Sampled Temporal Data. - Ronald Moore; Rishikesan Kamaleswaran (CoRR, 2022)

A Machine Learning-Enabled Partially Observable Markov Decision Process Framework for Early Sepsis Prediction. - Zeyu Liu 002; Anahita Khojandi; Xueping Li; Akram Mohammed; Robert L. Davis; Rishikesan Kamaleswaran (INFORMS J. Comput., 2022)

A Wearable Multimodal Sensing System for Tracking Changes in Pulmonary Fluid Status, Lung Sounds, and Respiratory Markers. - Jesus Antonio Sanchez-Perez; John A. Berkebile; Brandi N. Nevius; Goktug C. Ozmen; Christopher J. Nichols; Venu G. Ganti; Samer Mabrouk; Gari D. Clifford; Rishikesan Kamaleswaran; David W. Wright 002; Omer T. Inan (Sensors, 2022)

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection. - Anni Zhou; Raheem Beyah; Rishikesan Kamaleswaran (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes. - Song Wei; Yao Xie 002; Christopher S. Josef; Rishikesan Kamaleswaran (KDD, 2023)

Transfer Causal Learning: Causal Effect Estimation with Knowledge Transfer. - Song Wei; Ronald Moore; Hanyu Zhang; Yao Xie 002; Rishikesan Kamaleswaran (CoRR, 2023)

Mixed-Integer Projections for Automated Data Correction of EMRs Improve Predictions of Sepsis among Hospitalized Patients. - Mehak Arora; Hassan Mortagy; Nathan Dwarshius; Swati Gupta 001; Andre L. Holder; Rishikesan Kamaleswaran (CoRR, 2023)

Detecting algorithmic bias in medical AI-models. - Jeffrey Smith; Andre L. Holder; Rishikesan Kamaleswaran; Yao Xie 002 (CoRR, 2023)

Causal Graph Discovery From Self and Mutually Exciting Time Series. - Song Wei; Yao Xie 002; Christopher S. Josef; Rishikesan Kamaleswaran (IEEE J. Sel. Areas Inf. Theory, 2023)

Synthetic seismocardiogram generation using a transformer-based neural network. - Mohammad Nikbakht; Asim Hossain Gazi; Jonathan Zia; Sungtae An; David Jimmy Lin; Omer T. Inan; Rishikesan Kamaleswaran (J. Am. Medical Informatics Assoc., 2023)

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports. - Jeffrey Wang; Joao Souza de Vale; Saransh Gupta; Pulakesh Upadhyaya; Felipe A. Lisboa; Seth A. Schobel; Eric A. Elster; Christopher J. Dente; Timothy G. Buchman; Rishikesan Kamaleswaran (BMC Medical Informatics Decis. Mak., 2023)

Enabling Continuous Breathing-Phase Contextualization via Wearable-Based Impedance Pneumography and Lung Sounds: A Feasibility Study. - Jesus Antonio Sanchez-Perez; Asim Hossain Gazi; Samer A. Mabrouk; John A. Berkebile; Goktug C. Ozmen; Rishikesan Kamaleswaran; Omer T. Inan (IEEE J. Biomed. Health Informatics, 2023)

Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing. - Seibi Kobara; Alireza Rafiei; Masoud Nateghi; Selen Bozkurt; Rishikesan Kamaleswaran; Abeed Sarker (AIME (1), 2024)

Parsimonious waveform-derived features consisting of pulse arrival time and heart rate variability predicts the onset of septic shock. - Moamen Soliman; Curtis Marshall; Jacob P. Kimball; Tilendra Choudhary; Gilles Clermont; Michael R. Pinsky; Timothy G. Buchman; Craig M. Coopersmith; Omer T. Inan; Rishikesan Kamaleswaran (Biomed. Signal Process. Control., 2024)

Riemannian manifold-based geometric clustering of continuous glucose monitoring to improve personalized diabetes management. - Jiafeng Song; Jocelyn McNeany; Yifei Wang; Tanicia Daley; Arlene Stecenko; Rishikesan Kamaleswaran (Comput. Biol. Medicine, 2024)

Robust Meta-Model for Predicting the Need for Blood Transfusion in Non-traumatic ICU Patients. - Alireza Rafiei; Ronald Moore; Tilendra Choudhary; Curtis Marshall; Geoffrey Smith; John D. Roback; Ravi M. Patel; Cassandra D. Josephson; Rishikesan Kamaleswaran (CoRR, 2024)

Deep Representation Learning-Based Dynamic Trajectory Phenotyping for Acute Respiratory Failure in Medical Intensive Care Units. - Alan Wu; Tilendra Choudhary; Pulakesh Upadhyaya; Ayman Ali; Philip Yang; Rishikesan Kamaleswaran (CoRR, 2024)

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. - Alireza Rafiei; Milad Ghiasi Rad; Andrea Sikora; Rishikesan Kamaleswaran (Comput. Biol. Medicine, 2024)

Meta-learning in Healthcare: A Survey. - Alireza Rafiei; Ronald Moore; Sina Jahromi; Farshid Hajati; Rishikesan Kamaleswaran (SN Comput. Sci., 2024)

Evaluating the impact of common clinical confounders on performance of deep-learning-based sepsis risk assessment. - Shikha Chaganti; Vivek Singh; Alasdair Edward Gent; Rishikesan Kamaleswaran; Ali Kamen (Frontiers Artif. Intell., 2025)

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. - Milad Ghiasi Rad; Alireza Rafiei; Jocelyn Grunwell; Rishikesan Kamaleswaran (Int. J. Medical Informatics, 2025)

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS). - Ashwin Pathak; Curtis Marshall; Carolyn Davis; Philip Yang; Rishikesan Kamaleswaran (IEEE J. Biomed. Health Informatics, 2025)

Sepsyn-OLCP: An Online Learning-based Framework for Early Sepsis Prediction with Uncertainty Quantification using Conformal Prediction. - Anni Zhou; Beyah Raheem; Rishikesan Kamaleswaran; Yao Xie 002 (CoRR, 2025)

NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis Prediction. - Anni Zhou; Raheem Beyah; Rishikesan Kamaleswaran (CoRR, 2025)

Contextual Phenotyping of Pediatric Sepsis Cohort Using Large Language Models. - Aditya Nagori; Ayush Gautam; Matthew O. Wiens; Vuong Nguyen; Nathan Kenya Mugisha; Jerome Kabakyenga; Niranjan Kissoon; John Mark Ansermino; Rishikesan Kamaleswaran (CoRR, 2025)

Evaluating LLMs in Medicine: A Call for Rigor, Transparency. - Mahmoud Alwakeel; Aditya Nagori; Vijay Krishnamoorthy; Rishikesan Kamaleswaran (CoRR, 2025)

CXR-TFT: Multi-Modal Temporal Fusion Transformer for Predicting Chest X-ray Trajectories. - Mehak Arora; Ayman Ali; Kaiyuan Wu; Carolyn Davis; Takashi Shimazui; Mahmoud Alwakeel; Victor Moas; Philip Yang; Annette Esper; Rishikesan Kamaleswaran (CoRR, 2025)

Benchmarking Foundation Models with Multimodal Public Electronic Health Records. - Kunyu Yu; Rui Yang; Jingchi Liao; Siqi Li 004; Huitao Li; Irene Li; Yifan Peng; Rishikesan Kamaleswaran; Nan Liu 003 (CoRR, 2025)

Open-Source Agentic Hybrid RAG Framework for Scientific Literature Review. - Aditya Nagori; Ricardo Accorsi Casonatto; Ayush Gautam; Abhinav Manikantha Sai Cheruvu; Rishikesan Kamaleswaran (CoRR, 2025)