Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Saransh Gupta"'
Autor:
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
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-9 (2023)
Abstract Introduction Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classification of disease
Externí odkaz:
https://doaj.org/article/eada8457c36d414486e237c64e82fcb4
Publikováno v:
Asian Spine Journal, Vol 15, Iss 4, Pp 431-440 (2021)
Study Design Retrospective study of patients with lumbar canal stenosis (LCS) operated using endoscopic unilateral laminotomy with bilateral decompression (ULBD). Purpose This study aimed to provide a detailed description of the technique of endoscop
Externí odkaz:
https://doaj.org/article/7229c53f317a4535bff64efe7573e5a6
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Brain-inspired Hyper-dimensional(HD) computing is a novel and efficient computing paradigm. However, highly parallel architectures such as Processing-in-Memory(PIM) are bottle-necked by reduction operations required such as accumulation. To reduce th
Externí odkaz:
https://doaj.org/article/8d9e29a275f54d51b88bdf2df16d9b7c
Autor:
Quanquan Pang, Jiashen Meng, Saransh Gupta, Xufeng Hong, Chun Yuen Kwok, Ji Zhao, Yingxia Jin, Like Xu, Ozlem Karahan, Ziqi Wang, Spencer Toll, Liqiang Mai, Linda F. Nazar, Mahalingam Balasubramanian, Badri Narayanan, Donald R. Sadoway
Publikováno v:
Nature. 608:704-711
Autor:
Saransh Gupta, Behnam Khaleghi, Sahand Salamat, Justin Morris, Ranganathan Ramkumar, Jeffrey Yu, Aniket Tiwari, Jaeyoung Kang, Mohsen Imani, Baris Aksanli, Tajana Šimunić Rosing
Publikováno v:
ACM Transactions on Embedded Computing Systems. 21:1-25
Processing large amounts of data, especially in learning algorithms, poses a challenge for current embedded computing systems. Hyperdimensional (HD) computing (HDC) is a brain-inspired computing paradigm that works with high-dimensional vectors calle
Autor:
Chirag Agarwal, Saransh Gupta, Muhammad Najjar, Terri E. Weaver, Xiaohong Joe Zhou, Dan Schonfeld, Bharati Prasad
Publikováno v:
Sleep Vigil
PURPOSE: Persistent sustained attention deficit (SAD) after continuous positive airway pressure (CPAP) treatment is a source of quality of life and occupational impairment in obstructive sleep apnea (OSA). However, persistent SAD is difficult to pred
Autor:
Saransh Gupta, Mohsen Imani, Joonseop Sim, Andrew Huang, Fan Wu, Jaeyoung Kang, Yeseong Kim, Tajana Šimunić Rosing
Publikováno v:
ACM Journal on Emerging Technologies in Computing Systems. 18:1-25
Stochastic computing (SC) reduces the complexity of computation by representing numbers with long streams of independent bits. However, increasing performance in SC comes with either an increase in area or a loss in accuracy. Processing in memory (PI
Publikováno v:
Proceedings of International Conference on Data Science and Applications ISBN: 9789811966330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68d2c2c2b7249e0ae50a3cba159fb0da
https://doi.org/10.1007/978-981-19-6634-7_37
https://doi.org/10.1007/978-981-19-6634-7_37
Autor:
Saransh Gupta, Haswanth Vundavilli, Rodolfo S. Allendes Osorio, Mari N. Itoh, Attayeb Mohsen, Aniruddha Datta, Kenji Mizuguchi, Lokesh P. Tripathi
Publikováno v:
IEEE journal of biomedical and health informatics. 26(9)
Non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer and a leading cause of cancer-related deaths worldwide. Using an integrative approach, we analyzed a publicly available merged NSCLC transcriptome dataset using machine lear
Autor:
Anna L. Silverman, Balu Bhasuran, Arman Mosenia, Fatema Yasini, Saransh Gupta, Taline Mardirossian, Rohan Narain, Justin Sewell, Atul J. Butte, Vivek A. Rudrapatna
ImportanceElectronic health records (EHR) data are growing in importance as a source of evidence on real-world treatment effects. However, many clinical important measures are not directly captured as structured data by these systems, limiting their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5ce964653c77a18241ca2de7feee93f
https://doi.org/10.1101/2022.06.19.22276606
https://doi.org/10.1101/2022.06.19.22276606