Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study

OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis. DESIGN: A graph neural network was developed incorporating pathologist domain knowledge to classify 6591 whole-s...

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Detalles Bibliográficos
Autores principales: Graham, Simon, Minhas, Fayyaz, Bilal, Mohsin, Ali, Mahmoud, Tsang, Yee Wah, Eastwood, Mark, Wahab, Noorul, Jahanifar, Mostafa, Hero, Emily, Dodd, Katherine, Sahota, Harvir, Wu, Shaobin, Lu, Wenqi, Azam, Ayesha, Benes, Ksenija, Nimir, Mohammed, Hewitt, Katherine, Bhalerao, Abhir, Robinson, Andrew, Eldaly, Hesham, Raza, Shan E Ahmed, Gopalakrishnan, Kishore, Snead, David, Rajpoot, Nasir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Colon
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423541/
https://www.ncbi.nlm.nih.gov/pubmed/37173125
http://dx.doi.org/10.1136/gutjnl-2023-329512

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423541/
https://www.ncbi.nlm.nih.gov/pubmed/37173125
http://dx.doi.org/10.1136/gutjnl-2023-329512

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