Zobrazeno 1 - 10
of 199
pro vyhledávání: '"Pratheeksha"'
Publikováno v:
Journal of Orthopaedic Reports, Vol 2, Iss 4, Pp 100211- (2023)
Background: Maintaining balance control is crucial for dancers, particularly in classical dance, where intricate and dynamic movements are performed. The dynamic leap and balance test (DLBT) is commonly used to assess balance in dancers. However, the
Externí odkaz:
https://doaj.org/article/02b370d521754ae28eae9aff2ebf8237
Autor:
Ghafouri, Bijean, Mohammadzadeh, Shahrad, Zhou, James, Nair, Pratheeksha, Tian, Jacob-Junqi, Goel, Mayank, Rabbany, Reihaneh, Godbout, Jean-François, Pelrine, Kellin
Large language models are increasingly relied upon as sources of information, but their propensity for generating false or misleading statements with high confidence poses risks for users and society. In this paper, we confront the critical problem o
Externí odkaz:
http://arxiv.org/abs/2411.06528
Publikováno v:
Future Journal of Pharmaceutical Sciences, Vol 7, Iss 1, Pp 1-18 (2021)
Abstract Background In March 2020, the World Health Organization declared the coronavirus disease 2019 as a global pandemic. Though antiviral drugs and antimalarial drugs are considered treatment options for treating coronavirus disease 2019 (COVID-1
Externí odkaz:
https://doaj.org/article/1c83b2873d2648f0bb6543643756a666
Autor:
Yue Li, Pratheeksha Nair, Xing Han Lu, Zhi Wen, Yuening Wang, Amir Ardalan Kalantari Dehaghi, Yan Miao, Weiqi Liu, Tamas Ordog, Joanna M. Biernacka, Euijung Ryu, Janet E. Olson, Mark A. Frye, Aihua Liu, Liming Guo, Ariane Marelli, Yuri Ahuja, Jose Davila-Velderrain, Manolis Kellis
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-17 (2020)
Electronic Health Records (EHR) are subject to noise, biases and missing data. Here, the authors present MixEHR, a multi-view Bayesian framework related to collaborative filtering and latent topic models for EHR data integration and modeling.
Externí odkaz:
https://doaj.org/article/f93fdf7cc75646b5afb46727b4bdaa9e
Autor:
Zhi Wen, Pratheeksha Nair, Chih-Ying Deng, Xing Han Lu, Edward Moseley, Naomi George, Charlotta Lindvall, Yue Li
Publikováno v:
PLoS ONE, Vol 16, Iss 4, p e0249622 (2021)
Latent knowledge can be extracted from the electronic notes that are recorded during patient encounters with the health system. Using these clinical notes to decipher a patient's underlying comorbidites, symptom burdens, and treatment courses is an o
Externí odkaz:
https://doaj.org/article/fc33aa6759404983af0d17cb443d7972
Autor:
Pratheeksha Koppa Raghu, Kuldeep K. Bansal, Pradip Thakor, Valamla Bhavana, Jitender Madan, Jessica M. Rosenholm, Neelesh Kumar Mehra
Publikováno v:
Pharmaceuticals, Vol 13, Iss 8, p 167 (2020)
The topical route is the most preferred one for administering drugs to eyes, skin and wounds for reaching enhanced efficacy and to improve patient compliance. Topical administration of drugs via conventional dosage forms such as solutions, creams and
Externí odkaz:
https://doaj.org/article/e159e34dae6640b5978e06963833f27d
Autor:
Kiran, R., Pratheeksha, H.M., Saraswathi A, Vidya, Princy, A., Kennedy, S Masilla Moses, Altowyan, Abeer S., Sayyed, M.I., Kamath, Sudha D.
Publikováno v:
In Journal of Solid State Chemistry September 2024 337
In Reinforcement Learning (RL), Convolutional Neural Networks(CNNs) have been successfully applied as function approximators in Deep Q-Learning algorithms, which seek to learn action-value functions and policies in various environments. However, to d
Externí odkaz:
http://arxiv.org/abs/2007.03437
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Akademický článek
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