Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Aakash Kaku"'
Autor:
Boyang Yu, Aakash Kaku, Kangning Liu, Avinash Parnandi, Emily Fokas, Anita Venkatesan, Natasha Pandit, Rajesh Ranganath, Heidi Schambra, Carlos Fernandez-Granda
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract Automatic assessment of impairment and disease severity is a key challenge in data-driven medicine. We propose a framework to address this challenge, which leverages AI models trained exclusively on healthy individuals. The COnfidence-Based
Externí odkaz:
https://doaj.org/article/1ddf15b7328c42eeb76a6aaeab726819
Autor:
Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanisław Jastrzębski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
Publikováno v:
npj Digital Medicine, Vol 4, Iss 1, Pp 1-11 (2021)
Abstract During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration ris
Externí odkaz:
https://doaj.org/article/39490bddaa344a02b06a3d77ab46dd52
Autor:
Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Emily Fokas, Boyang Yu, Grace Kim, Dawn Nilsen, Carlos Fernandez-Granda, Heidi Schambra
Publikováno v:
Bioengineering, Vol 10, Iss 6, p 648 (2023)
Stroke commonly affects the ability of the upper extremities (UEs) to move normally. In clinical settings, identifying and measuring movement abnormality is challenging due to the imprecision and impracticality of available assessments. These challen
Externí odkaz:
https://doaj.org/article/719b3608b75242bc9ff31a84ba118fe7
Autor:
Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Audre Wirtanen, Haresh Rajamohan, Kannan Venkataramanan, Dawn Nilsen, Carlos Fernandez-Granda, Heidi Schambra
Publikováno v:
PLOS Digital Health, Vol 1, Iss 6, p e0000044 (2022)
Stroke rehabilitation seeks to accelerate motor recovery by training functional activities, but may have minimal impact because of insufficient training doses. In animals, training hundreds of functional motions in the first weeks after stroke can su
Externí odkaz:
https://doaj.org/article/3a31e0609a8e4dfba73e3d52b9b83593
Autor:
Avinash Parnandi, Aakash Kaku, Anita Venkatesan, Natasha Pandit, Audre Wirtanen, Haresh Rajamohan, Kannan Venkataramanan, Dawn Nilsen, Carlos Fernandez-Granda, Heidi Schambra
Stroke rehabilitation seeks to accelerate motor recovery by training functional activities, but may have minimal impact because of insufficient training doses. In animals, training hundreds of functional motions in the first weeks after stroke can su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbbcc60d01eadd3e847bfecb412aa98a
Autor:
Aakash, Kaku, Avinash, Parnandi, Anita, Venkatesan, Natasha, Pandit, Heidi, Schambra, Carlos, Fernandez-Granda
Publikováno v:
Proc Mach Learn Res
Recovery after stroke is often incomplete, but rehabilitation training may potentiate recovery by engaging endogenous neuroplasticity. In preclinical models of stroke, high doses of rehabilitation training are required to restore functional movement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::def6fe0b0514f7b7f8befe4759ff056f
https://pubmed.ncbi.nlm.nih.gov/34337420
https://pubmed.ncbi.nlm.nih.gov/34337420
Autor:
Meng Cao, Yindalon Aphinyanaphongs, Jan Witowski, Carlos Fernandez-Granda, Yiqiu Shen, Siddhant Dogra, Duo Wang, Jungkyu Park, Narges Razavian, David Kudlowitz, Krzysztof J. Geras, Yvonne W. Lui, Farah E. Shamout, Nan Wu, Lea Azour, Aakash Kaku, Stanisław Jastrzębski, William Moore, Taro Makino, Ben Zhang
Publikováno v:
ArXiv
npj Digital Medicine, Vol 4, Iss 1, Pp 1-11 (2021)
NPJ Digital Medicine
npj Digital Medicine, Vol 4, Iss 1, Pp 1-11 (2021)
NPJ Digital Medicine
During the coronavirus disease 2019 (COVID-19) pandemic, rapid and accurate triage of patients at the emergency department is critical to inform decision-making. We propose a data-driven approach for automatic prediction of deterioration risk using a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f39f3f0742be77aea34cfa88df9262d
https://europepmc.org/articles/PMC7418753/
https://europepmc.org/articles/PMC7418753/