Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Subba R. Digumarthy"'
Autor:
Bernardo C. Bizzo, Shadi Ebrahimian, Mark E. Walters, Mark H. Michalski, Katherine P. Andriole, Keith J. Dreyer, Mannudeep K. Kalra, Tarik Alkasab, Subba R. Digumarthy
Publikováno v:
PloS one. 17(4)
A standardized objective evaluation method is needed to compare machine learning (ML) algorithms as these tools become available for clinical use. Therefore, we designed, built, and tested an evaluation pipeline with the goal of normalizing performan
Autor:
Fatemeh Homayounieh, Rosa Babaei, Subba R. Digumarthy, Anderson H. Kuo, Chiara Arru, Hadi Karimi Mobin, Iman Mohseni, Maedeh Sharifian, Eric W. Zhang, Mannudeep K. Kalra
Publikováno v:
PLoS ONE
PLOS ONE, 15(9):e0239519
PLoS ONE, Vol 15, Iss 9, p e0239519 (2020)
PLOS ONE, 15(9):e0239519
PLoS ONE, Vol 15, Iss 9, p e0239519 (2020)
The new coronavirus disease 2019 (COVID-19) pandemic has challenged many healthcare systems around the world. While most of the current understanding of the clinical features of COVID-19 is derived from Chinese studies, there is a relative paucity of
Autor:
Victorine V. Muse, Atul Padole, Subba R. Digumarthy, Fatemeh Homayounieh, Pooja Rao, Mannudeep K. Kalra, Chayanin Nitiwarangkul, Preetham Putha, Ramandeep Singh, Amita Sharma, John A. Patti
Publikováno v:
PLoS ONE
PLoS ONE, Vol 13, Iss 10, p e0204155 (2018)
PLoS ONE, Vol 13, Iss 10, p e0204155 (2018)
Background Deep learning (DL) based solutions have been proposed for interpretation of several imaging modalities including radiography, CT, and MR. For chest radiographs, DL algorithms have found success in the evaluation of abnormalities such as lu
Autor:
Bernardo C Bizzo, Shadi Ebrahimian, Mark E Walters, Mark H Michalski, Katherine P Andriole, Keith J Dreyer, Mannudeep K Kalra, Tarik Alkasab, Subba R Digumarthy
Publikováno v:
PLoS ONE, Vol 17, Iss 4, p e0267213 (2022)
A standardized objective evaluation method is needed to compare machine learning (ML) algorithms as these tools become available for clinical use. Therefore, we designed, built, and tested an evaluation pipeline with the goal of normalizing performan
Externí odkaz:
https://doaj.org/article/0f56a7d673ec4cba8fb032ce0553968f
Autor:
Ramandeep Singh, Mannudeep K Kalra, Chayanin Nitiwarangkul, John A Patti, Fatemeh Homayounieh, Atul Padole, Pooja Rao, Preetham Putha, Victorine V Muse, Amita Sharma, Subba R Digumarthy
Publikováno v:
PLoS ONE, Vol 13, Iss 10, p e0204155 (2018)
BACKGROUND:Deep learning (DL) based solutions have been proposed for interpretation of several imaging modalities including radiography, CT, and MR. For chest radiographs, DL algorithms have found success in the evaluation of abnormalities such as lu
Externí odkaz:
https://doaj.org/article/d062da2c436d49b68af1771ed751fb0a