Publications

Publications

Journal Articles and Conference Proceedings

  • [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, Rafi Ahamed S. “Editorial: Smart biomedical signal analysis with machine intelligence.” Front. Signal Process, 2025, 5:1555876.

  • [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, 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, 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 Alzheimer’s Disease Using Deep Learning,” IEEE 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.” JMIR Med Inform, 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,” J Biomed Inform, 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,” ITA Workshop, 2020.

  • [c4] N. Raviv, S. Jain, P. Upadhyaya, J. Bruck, A. Jiang. “CodNN: Robust Neural Networks From Coded Classification,” IEEE ISIT, 2020.

  • [w8] N. Raviv, P. Upadhyaya, S. Jain, J. Bruck, A. Jiang. “Coded Deep Neural Networks for Robust Neural Computation,” NVMW, 2020.

  • [c3] P. Upadhyaya, A. Jiang. “Representation-Oblivious Error Correction by Natural Redundancy,” IEEE ICC, Shanghai, 2019.

  • [w7] P. Upadhyaya, A. Jiang. “File Type Recognition and Error Correction for NVMs with Deep Learning,” NVMW, 2019.

  • [w6] P. Upadhyaya, X. Yu, J. Mink, J. Cordero, P. Parmar, A. Jiang. “Error Correction for Hardware-Implemented Deep Neural Networks,” NVMW, 2019.

  • [w5] P. Upadhyaya, X. Yu, J. Mink, J. Cordero, P. Parmar, A. Jiang. “Error Correction for Noisy Neural Networks,” ITA Workshop, 2019.

  • [w4] A. Jiang, P. Upadhyaya, Y. Wang, K. Narayanan, H. Zhou, J. Sima, J. Bruck. “Efficient Assistance to LDPC Code-based Erasure Recovery in NVM Storage,” NVMW, 2018.

  • [c2] P. Upadhyaya, A. Jiang. “On LDPC Decoding with Natural Redundancy,” Allerton Conference, 2017.

  • [c1] A. Jiang, P. Upadhyaya, Y. Li, K. Narayanan, H. Zhou, J. Sima, J. Bruck. “Stopping Set Elimination for LDPC Codes,” Allerton Conference, 2017.

  • [w3] A. Jiang, P. Upadhyaya, E.F. Haratsch, J. Bruck. “Error Correction by Natural Redundancy for Long Term Storage,” NVMW, 2017.

  • [w2] P. Upadhyaya, A. Jiang. “LDPC Decoding with Natural Redundancy,” NVMW, 2017.

  • [w1] A. Jiang, P. Upadhyaya, E.F. Haratsch, J. Bruck. “Correcting Errors by Natural Redundancy,” ITA Workshop, 2017.

  • [j1] S. Nair, P. Upadhyaya, V.M. Tom. “A Dynamic Offset Model based on Stop Line Detector Information.” Procedia - Social and Behavioral Sciences, 104, 487–496, 2013.

Preprints and 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.