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Medical Image Analysis
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May 31, 2022
SlideGraph<sup>+</sup>: Whole slide image level graphs to predict HER2 status in breast cancer
Wenqi Lu, Michael Toss, Muhammad Dawood, et al.
Journal of Clinical Pathology
|
September 15, 2022
Using Systemised Nomenclature of Medicine (SNOMED) codes to select digital pathology whole slide images for long-term archiving
Mahmoud Ali, Harriet Evans, Peter Whitney, et al.
The Journal of Pathology
|
August 8, 2023
Unleashing the potential of AI for pathology: challenges and recommendations
Amina Asif, Kashif Rajpoot, Simon Graham, et al.
Histopathology
|
November 9, 2022
Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading
Asmaa Ibrahim, Michael S Toss, Shorouk Makhlouf, et al.
Medical Image Analysis
|
March 5, 2024
Mitosis detection, fast and slow: Robust and efficient detection of mitotic figures
Mostafa Jahanifar, Adam Shephard, Neda Zamanitajeddin, et al.
Medical Image Analysis
|
November 21, 2022
One model is all you need: Multi-task learning enables simultaneous histology image segmentation and classification
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, et al.
The Journal of Pathology
|
January 27, 2023
Artificial intelligence-based digital scores of stromal tumour-infiltrating lymphocytes and tumour-associated stroma predict disease-specific survival in triple-negative breast cancer
Rawan Albusayli, J Dinny Graham, Nirmala Pathmanathan, et al.
Scientific Reports
|
May 13, 2022
Lessons from a breast cell annotation competition series for school pupils
Wenqi Lu, Islam M Miligy, Fayyaz Minhas, et al.
The Lancet. Digital Health
|
October 23, 2021
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study
Mohsin Bilal, Shan E Ahmed Raza, Ayesha Azam, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
January 24, 2021
Deep learning based digital cell profiles for risk stratification of urine cytology images
Ruqayya Awan, Ksenija Benes, Ayesha Azam, et al.
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of 4
Search research articles
Search
Showing results (11-20 of 39) with videos related to
Sort By:
Page
of 4
Medical Image Analysis
|
May 31, 2022
SlideGraph<sup>+</sup>: Whole slide image level graphs to predict HER2 status in breast cancer
Wenqi Lu, Michael Toss, Muhammad Dawood, et al.
Journal of Clinical Pathology
|
September 15, 2022
Using Systemised Nomenclature of Medicine (SNOMED) codes to select digital pathology whole slide images for long-term archiving
Mahmoud Ali, Harriet Evans, Peter Whitney, et al.
The Journal of Pathology
|
August 8, 2023
Unleashing the potential of AI for pathology: challenges and recommendations
Amina Asif, Kashif Rajpoot, Simon Graham, et al.
Histopathology
|
November 9, 2022
Improving mitotic cell counting accuracy and efficiency using phosphohistone-H3 (PHH3) antibody counterstained with haematoxylin and eosin as part of breast cancer grading
Asmaa Ibrahim, Michael S Toss, Shorouk Makhlouf, et al.
Medical Image Analysis
|
March 5, 2024
Mitosis detection, fast and slow: Robust and efficient detection of mitotic figures
Mostafa Jahanifar, Adam Shephard, Neda Zamanitajeddin, et al.
Medical Image Analysis
|
November 21, 2022
One model is all you need: Multi-task learning enables simultaneous histology image segmentation and classification
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, et al.
The Journal of Pathology
|
January 27, 2023
Artificial intelligence-based digital scores of stromal tumour-infiltrating lymphocytes and tumour-associated stroma predict disease-specific survival in triple-negative breast cancer
Rawan Albusayli, J Dinny Graham, Nirmala Pathmanathan, et al.
Scientific Reports
|
May 13, 2022
Lessons from a breast cell annotation competition series for school pupils
Wenqi Lu, Islam M Miligy, Fayyaz Minhas, et al.
The Lancet. Digital Health
|
October 23, 2021
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study
Mohsin Bilal, Shan E Ahmed Raza, Ayesha Azam, et al.
Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|
January 24, 2021
Deep learning based digital cell profiles for risk stratification of urine cytology images
Ruqayya Awan, Ksenija Benes, Ayesha Azam, et al.
Page
of 4