Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Kiret Dhindsa"'
Autor:
Paul Triebkorn, Leon Stefanovski, Kiret Dhindsa, Margarita‐Arimatea Diaz‐Cortes, Patrik Bey, Konstantin Bülau, Roopa Pai, Andreas Spiegler, Ana Solodkin, Viktor Jirsa, Anthony Randal McIntosh, Petra Ritter, for the Alzheimer's Disease Neuroimaging Initiative
Publikováno v:
Alzheimer’s & Dementia: Translational Research & Clinical Interventions, Vol 8, Iss 1, Pp n/a-n/a (2022)
ABSTRACT Introduction Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning (ML) and multi‐modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer's di
Externí odkaz:
https://doaj.org/article/4adceb43ebdd479689cbc6d744721ac7
Publikováno v:
Frontiers in Pediatrics, Vol 8 (2020)
Grading hydronephrosis severity relies on subjective interpretation of renal ultrasound images. Deep learning is a data-driven algorithmic approach to classifying data, including images, presenting a promising option for grading hydronephrosis. The c
Externí odkaz:
https://doaj.org/article/51c4731baa6b4a32a1e18b4d9b4efc7d
Autor:
Kiret Dhindsa, Anita Acai, Natalie Wagner, Dan Bosynak, Stephen Kelly, Mohit Bhandari, Brad Petrisor, Ranil R Sonnadara
Publikováno v:
PLoS ONE, Vol 14, Iss 9, p e0222276 (2019)
Neural correlates of mind wanderingThe ability to detect mind wandering as it occurs is an important step towards improving our understanding of this phenomenon and studying its effects on learning and performance. Current detection methods typically
Externí odkaz:
https://doaj.org/article/d29dfe7919ca449883361983e36b7ef5
Autor:
Umaseh Sivanesan, Kay Wu, Matthew D. F. McInnes, Kiret Dhindsa, Fateme Salehi, Christian B. van der Pol
Publikováno v:
Canadian Association of Radiologists Journal. 74:334-342
Purpose: To establish reporting adherence to the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) in diagnostic accuracy AI studies with the highest Altmetric Attention Scores (AAS), and to compare completeness of reporting between pe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26a515c2de5b551f17d5d109b8f21ad7
https://doi.org/10.1177/08465371221134056
https://doi.org/10.1177/08465371221134056
Autor:
Julian G. Rubino, Amir Reza Nasirzadeh, Christian B. van der Pol, Kiret Dhindsa, Andrew D. Chung
Publikováno v:
Abdominal Radiology. 47:2314-2324
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5246a9730d5cf9b9734e3734abd085ed
https://doi.org/10.1007/s00261-022-03550-0
https://doi.org/10.1007/s00261-022-03550-0
Autor:
Amar Udare, Minu Agarwal, Kiret Dhindsa, Amer Alaref, Michael Patlas, Abdullah Alabousi, Yoan K. Kagoma, Christian B. van der Pol
Publikováno v:
J Digit Imaging
The purpose is to determine factors impacting radiologist abdominal pelvic CT exam reporting time. This study was Research Ethics Board approved. Between January 2019 and March 2020, consecutive abdominal pelvic CT exams were documented as structured
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78296a2574c86863ae8feca518ae2e37
https://doi.org/10.1007/s10278-021-00548-w
https://doi.org/10.1007/s10278-021-00548-w
Autor:
Christian B. van der Pol, Radu Rozenberg, Ameya Kulkarni, Amer Alaref, Ivan Carrion-Martinez, Kiret Dhindsa
Publikováno v:
Abdominal Radiology. 46:1027-1033
To determine equivalency of multi-slice 3D CTTA and single slice 2D CTTA of pancreas adenocarcinoma. This retrospective study was research ethics board approved. Untreated pancreas adenocarcinomas were segmented on CT in 128 consecutive patients. Tum
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cba16166de07000c0e30313a01c8144
https://doi.org/10.1007/s00261-020-02759-1
https://doi.org/10.1007/s00261-020-02759-1
Publikováno v:
2022 10th International Winter Conference on Brain-Computer Interface (BCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fa962f2162f841acfe76e1e18860095
https://doi.org/10.1109/bci53720.2022.9735007
https://doi.org/10.1109/bci53720.2022.9735007
Autor:
Paul, Triebkorn, Leon, Stefanovski, Kiret, Dhindsa, Margarita-Arimatea, Diaz-Cortes, Patrik, Bey, Konstantin, Bülau, Roopa, Pai, Andreas, Spiegler, Ana, Solodkin, Viktor, Jirsa, Anthony Randal, McIntosh, Petra, Ritter
Publikováno v:
Alzheimer's & Dementia: Translational Research & Clinical Interventions
Alzheimer's & Dementia: Translational Research & Clinical Interventions, 2022, 8 (1), ⟨10.1002/trc2.12303⟩
Alzheimer's & Dementia: Translational Research & Clinical Interventions, 2022, 8 (1), ⟨10.1002/trc2.12303⟩
Computational brain network modeling using The Virtual Brain (TVB) simulation platform acts synergistically with machine learning (ML) and multi-modal neuroimaging to reveal mechanisms and improve diagnostics in Alzheimer's disease (AD).We enhance la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9cb2dd4b9ce499ba24a4435c19bbf78c
https://pubmed.ncbi.nlm.nih.gov/35601598
https://pubmed.ncbi.nlm.nih.gov/35601598
Autor:
Omar Boursalie, John F. Connolly, James P. Reilly, Kiret Dhindsa, Rober Boshra, Thomas E. Doyle, Reza Samavi, Ranil Sonnadara, Kyle I. Ruiter
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27:1492-1501
There has been increased effort to understand the neurophysiological effects of concussion aimed to move diagnosis and identification beyond current subjective behavioral assessments that suffer from poor sensitivity. Recent evidence suggests that ev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ee63b033193d27a1b355afad95e4efe
https://doi.org/10.1109/tnsre.2019.2922553
https://doi.org/10.1109/tnsre.2019.2922553