Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Siddhesh P. Thakur"'
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system that affects nearly 1 million adults in the United States. Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis and treatment monitoring in MS patients. In p
Externí odkaz:
https://doaj.org/article/108840d63d484a8a9329e05a0e7fc771
Autor:
Rhea Chitalia, Sarthak Pati, Megh Bhalerao, Siddhesh Pravin Thakur, Nariman Jahani, Vivian Belenky, Elizabeth S. McDonald, Jessica Gibbs, David C. Newitt, Nola M. Hylton, Despina Kontos, Spyridon Bakas
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-7 (2022)
Abstract Breast cancer is one of the most pervasive forms of cancer and its inherent intra- and inter-tumor heterogeneity contributes towards its poor prognosis. Multiple studies have reported results from either private institutional data or publicl
Externí odkaz:
https://doaj.org/article/ad25578784834782a0b3e405eb4c6a75
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Convolutional neural network (CNN) models obtain state of the art performance on image classification, localization, and segmentation tasks. Limitations in computer hardware, most notably memory size in deep learning accelerator cards, prevent relati
Externí odkaz:
https://doaj.org/article/691c87d5ea044890970c2ce4b9bce4d6
Autor:
Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid, Bhakti Baheti, Megh Bhalerao, Orhun Güley, Sofia Mouchtaris, David Lang, Spyridon Thermos, Karol Gotkowski, Camila González, Caleb Grenko, Alexander Getka, Brandon Edwards, Micah Sheller, Junwen Wu, Deepthi Karkada, Ravi Panchumarthy, Vinayak Ahluwalia, Chunrui Zou, Vishnu Bashyam, Yuemeng Li, Babak Haghighi, Rhea Chitalia, Shahira Abousamra, Tahsin M. Kurc, Aimilia Gastounioti, Sezgin Er, Mark Bergman, Joel H. Saltz, Yong Fan, Prashant Shah, Anirban Mukhopadhyay, Sotirios A. Tsaftaris, Bjoern Menze, Christos Davatzikos, Despina Kontos, Alexandros Karargyris, Renato Umeton, Peter Mattson, Spyridon Bakas
Publikováno v:
Communications Engineering. 2
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations hinders their reproducibility,