Publications

Preprints/Reports

[pr3] A Wu, T Choudhary, P. Upadhyaya, A Ali, P Yang, R Kamaleswaran. “Deep Representation Learning-Based Dynamic Trajectory Phenotyping for Acute Respiratory Failure in Medical Intensive Care Units,” arXiv preprint arXiv:2405.02563, 2024.

[pr2] DB Ramesh, RI Sridhar, P. Upadhyaya, R Kamaleswaran. “Lung Grounded-SAM (LuGSAM): A Novel Framework for Integrating Text prompts to Segment Anything Model (SAM) for Segmentation Tasks of ICU Chest X-Rays,” Authorea Preprints, 2023.

[pr1] P. Upadhyaya and A. Jiang, Machine Learning for Error Correction with Natural Redundancy, arXiv preprint  arXiv:1910.07420, 2019. 

Publications

[c11] P. Krishnan, A. Sikora, B. Murray, P. Upadhyaya, P. Yang, A.M. Esper, and R. Kamaleswaran. Multiscale Complexity Analysis for Vasopressor Treatment Effect Among Sepsis Patients [abstract]. Am J Respir Crit Care Med 2025;211:A5680. https://doi.org/10.1164/ajrccm.2025.211.Abstracts.A5680

[c10] Krishnan, P; Sikora, A; Upadhyaya, P; Murray, B; Yang, P; Esper, A; Kamaleswaran, R. 1047: MULTIMODAL TREATMENT EFFECT ON HEART RATE VARIABILITY AMONG VASOACTIVE MEDICATION USE IN SEPSIS. Critical Care Medicine 53(1):, January 2025. | DOI: 10.1097/01.ccm.0001102852.37247.d5

[j7] Choudhary T, Upadhyaya P, Parvez MZ and Rafi Ahamed S Editorial: Smart biomedical signal analysis with machine intelligence. Front. Signal Process (2025) . 5:1555876. doi: 10.3389/frsip.2025.1555876

[j6] P. Upadhyaya, J. Wang et al. “Predicting Sepsis Induced Hypotension Patient Attributes for Restrictive vs Liberal Fluid Strategy,” Shock, 2024.

[j5] T Choudhary, P. Upadhyaya, C. Davis, P. Yang, et al. “Derivation and validation of generalized sepsis-induced acute respiratory failure phenotypes among critically ill patients: a retrospective study,” Critical Care 28 (321), 2024.

[c9] T Choudhary, P. Upadhyaya, C Davis, P Yang, C Coopersmith, et al. “A Multicenter Study on Deriving and Validating Data-driven Phenotypes for Sepsis-induced Acute Respiratory Failure in ICU Patients,” C96. PRECISION MEDICINE IN CRITICAL CARE: EXPLORING ARDS AND SEPSIS, 2024.

[c8] P. Upadhyaya, T Choudhary, C Davis, P Yang, C Coopersmith, et al. “A Retrospective Causal Inference-based Study Using Machine Learning for Identifying Treatment Effects of Various Therapies in Sepsis-induced Acute Respiratory Failure Phenotypes,” C22. ARTIFICIAL INTELLIGENCE IN THE ICU: THE MACHINE WILL SEE YOU NOW, A5071, 2024.

[c7] P. Upadhyaya, J Wang, JS De Vale, F Lisboa, S Schobel, E Elster, et al. “1478: CHARACTERIZING SEPSIS-INDUCED HYPOTENSION PATIENTS WHO BENEFIT FROM AN EARLY VASOPRESSOR STRATEGY,” Critical Care Medicine 52 (1), S710, 2024.

[j4] J Wang, JS de Vale, S Gupta, P. Upadhyaya, FA Lisboa, SA Schobel, et al. “ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports,” BMC Medical Informatics and Decision Making 23 (1), 262, 2023.

[c6] Y Ling, P Upadhyaya,  L Chen, Y Kim, X Jiang “Inferring Personalized Treatment Effect of Antihypertensives on Alzheimers Disease Using Deep Learning”, IEEE International Conference on Healthcare Informatics (ICHI), 2023.

[j3] P Upadhyaya, K Zhang, C Li, X Jiang, Y Kim, “Scalable Causal Structure Learning: Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine.”, Journal of Medical Internet Research (Medical Informatics), 2022. 

[j2] Y Ling, P Upadhyaya, L Chen, X Jiang, Y Kim, "Emulate Randomized Clinical Trials using Heterogeneous Treatment Effect Estimation for Personalized Treatments: Methodology Review and Benchmark”, Journal of Biomedical Informatics, 2022. 

[c5] B. Wu, P. Upadhyaya, S. Savitz, X. Jiang, S. Shams, “Novel Machine-learning Analysis to Predict Outcomes During Inpatient Rehabilitation”, World Stroke Congress, 2021.

[w9] K. Huang, N. Raviv, S. Jain, P. Upadhyaya, J. Bruck, P.H. Siegel, A.A. Jiang,“Improve Robustness of Deep Neural Networks by Coding”, Proc. Information Theory and Applications Workshop (ITA) , 2020.

[c4] N. Raviv, S. Jain, P. Upadhyaya, J. Bruck, and A. Jiang, CodNN Robust Neural Networks From Coded Classification, to appear in Proc. IEEE International Symposium on Information Theory (ISIT), 2020.

[w8] N. Raviv, P. Upadhyaya, S. Jain, J. Bruck, and A. Jiang, Coded Deep Neural Networks for Robust Neural Computation, accepted by Annual Non-volatile Memories Workshop (NVMW), 2020.

[c3] P. Upadhyaya and A. Jiang, Representation-Oblivious Error Correction by Natural Redundancy, to appear in Proc. IEEE International Conference on Communications (ICC), Shanghai, China, May 2019. 

[w7] P. Upadhyaya and A. Jiang, File Type Recognition and Error Correction for NVMs with Deep Learning, to appear in Proc. Non-Volatile Memories Workshop (NVMW), La Jolla, CA, March 2019. 

[w6] P. Upadhyaya, X. Yu, J. Mink, J. Cordero, P. Parmar and A. Jiang, Error Correction for Hardware-Implemented Deep Neural Networks, to appear in Proc. Non-Volatile Memories Workshop (NVMW), La Jolla, CA, March 2019. 

[w5] P. Upadhyaya, X. Yu, J. Mink, J. Cordero, P. Parmar and A. Jiang, Error Correction for Noisy Neural Networks, to appear in Proc. Information Theory and Applications (ITA) Workshop, San Diego, CA, February 2019. 

[w4] A. Jiang, P. Upadhyaya, Y. Wang, K. R. Narayanan, H. Zhou, J. Sima and J. Bruck, Efficient Assistance to LDPC Code-based Erasure Recovery in NVM Storage, to appear in Proc. Non-Volatile Memories Workshop (NVMW), San Diego, CA, March 2018.

[c2] P. Upadhyaya and A. Jiang, On LDPC Decoding with Natural Redundancy, in Proc. 55th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, 2017.

[c1] A. Jiang, P. Upadhyaya,Y. Li, K. Narayanan, H. Zhou, J. Sima, J. Bruck, Stopping Set Elimination for LDPC Codes , in Proc. 55th Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, 2017.

[w3] A. Jiang, P. Upadhyaya, E. F. Haratsch and J. Bruck, Error Correction by Natural Redundancy for Long Term Storage, Proc. Non-Volatile Memories Workshop (NVMW), La Jolla, CA, March 2017.

[w2] P. Upadhyaya and A. Jiang, LDPC Decoding with Natural Redundancy, Proc. Non-Volatile Memories Workshop (NVMW), La Jolla, CA, March 2017.

[w1] A. Jiang, P. Upadhyaya, E. F. Haratsch and J. Bruck, Correcting Errors by Natural Redundancy, Proc. Information Theory and Applications (ITA) Workshop, San Diego, CA, February 2017.

[j1] S. Nair, P. Upadhyaya, and VM. Tom. "A Dynamic Offset Model based on Stop Line Detector Information." Procedia-Social and Behavioral Sciences 104 (2013): 487-496.