Zobrazeno 1 - 10
of 336
pro vyhledávání: '"Yee Wah So"'
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 5, p 2723 (2022)
Mutations of GABAAR have reportedly led to epileptic encephalopathy and neurodevelopmental disorders. We have identified a novel de novo T292S missense variant of GABRA1 from a pediatric patient with grievous global developmental delay but without ob
Externí odkaz:
https://doaj.org/article/692f15f801624ded9eb875d0cde54701
Autor:
Mark J Arends, Andrew Robinson, Kishore Gopalakrishnan, Eve Fryer, Betania Mahler-Araujo, Sonali Natu, Elizabeth J Soilleux, Gerald Langman, Kathryn J Kirkwood, EMYR W BENBOW, Caroline A Hughes, Yee Wah Tsang, James Denholm, Benjamin A Schreiber, Florian Jaeckle, Mike N Wicks, Tim S Bracey, James Y H Chan, Lorant Farkas, Raymond F T McMahon, Khun La Win Myint, Ashraf Sanduka, Katharine A Sheppard
Publikováno v:
BMJ Open Gastroenterology, Vol 11, Iss 1 (2024)
Objective Coeliac disease (CD) diagnosis generally depends on histological examination of duodenal biopsies. We present the first study analysing the concordance in examination of duodenal biopsies using digitised whole-slide images (WSIs). We furthe
Externí odkaz:
https://doaj.org/article/f255879a5c044f40853761bffd7965cc
Autor:
Graham, Simon, Jahanifar, Mostafa, Azam, Ayesha, Nimir, Mohammed, Tsang, Yee-Wah, Dodd, Katherine, Hero, Emily, Sahota, Harvir, Tank, Atisha, Benes, Ksenija, Wahab, Noorul, Minhas, Fayyaz, Raza, Shan E Ahmed, Daly, Hesham El, Gopalakrishnan, Kishore, Snead, David, Rajpoot, Nasir
The development of deep segmentation models for computational pathology (CPath) can help foster the investigation of interpretable morphological biomarkers. Yet, there is a major bottleneck in the success of such approaches because supervised deep le
Externí odkaz:
http://arxiv.org/abs/2108.11195
Autor:
Wahab, Noorul, Miligy, Islam M, Dodd, Katherine, Sahota, Harvir, Toss, Michael, Lu, Wenqi, Jahanifar, Mostafa, Bilal, Mohsin, Graham, Simon, Park, Young, Hadjigeorghiou, Giorgos, Bhalerao, Abhir, Lashen, Ayat, Ibrahim, Asmaa, Katayama, Ayaka, Ebili, Henry O, Parkin, Matthew, Sorell, Tom, Raza, Shan E Ahmed, Hero, Emily, Eldaly, Hesham, Tsang, Yee Wah, Gopalakrishnan, Kishore, Snead, David, Rakha, Emad, Rajpoot, Nasir, Minhas, Fayyaz
Recent advances in whole slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence (AI) based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an int
Externí odkaz:
http://arxiv.org/abs/2106.13689
To train a robust deep learning model, one usually needs a balanced set of categories in the training data. The data acquired in a medical domain, however, frequently contains an abundance of healthy patients, versus a small variety of positive, abno
Externí odkaz:
http://arxiv.org/abs/2003.03109
Akademický článek
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Autor:
Bilal, Mohsin *, Tsang, Yee Wah *, Ali, Mahmoud, Graham, Simon, Hero, Emily, Wahab, Noorul, Dodd, Katherine, Sahota, Harvir, Wu, Shaobin, Lu, Wenqi, Jahanifar, Mostafa, Robinson, Andrew, Azam, Ayesha, Benes, Ksenija, Nimir, Mohammed, Hewitt, Katherine, Bhalerao, Abhir, Eldaly, Hesham, Raza, Shan E Ahmed, Gopalakrishnan, Kishore, Minhas, Fayyaz, Snead, David, Rajpoot, Nasir *
Publikováno v:
In The Lancet Digital Health November 2023 5(11):e786-e797
Autor:
Graham, Simon, Vu, Quoc Dang, Raza, Shan E Ahmed, Azam, Ayesha, Tsang, Yee Wah, Kwak, Jin Tae, Rajpoot, Nasir
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of automated methods for nuclear segmentation and classification enables th
Externí odkaz:
http://arxiv.org/abs/1812.06499
Akademický článek
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Autor:
Graham, Simon, Chen, Hao, Gamper, Jevgenij, Dou, Qi, Heng, Pheng-Ann, Snead, David, Tsang, Yee Wah, Rajpoot, Nasir
Publikováno v:
Medical Image Analysis vol. 52, pp. 199-211, Feb. 2019
The analysis of glandular morphology within colon histopathology images is an important step in determining the grade of colon cancer. Despite the importance of this task, manual segmentation is laborious, time-consuming and can suffer from subjectiv
Externí odkaz:
http://arxiv.org/abs/1806.01963