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639 results on '"Ibrahim, Asmaa"'

20. Contextualizing the Discussion on Mosque Architecture in Today’s World

Author

Fekry, Mohammed, Mohamed, Mady A. A., Ibrahim, Asmaa, Visvizi, Anna, Ghamri, Lamiaa F., Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, O. Gawad, Iman, Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Fekry, Mohammed, editor, Mohamed, Mady A.A., editor, Visvizi, Anna, editor, Ibrahim, Asmaa, editor, and Ghamri, Lamiaa F., editor

Published
2023
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27. Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations

Author

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, and Minhas, Fayyaz

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

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 integrated solution to utilize information embedded in pathology WSIs beyond what we obtain through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms which are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well-defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large-scale annotation exercise involving a multidisciplinary team of pathologists, ML experts and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real-world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Published
2021

38. Introduction

Author

Mohamed, Mady, Fekry, Mohamed, Ibrahim, Asmaa, Mohamed, Mady, editor, Ibrahim, Asmaa, editor, and Fekry, Mohamed, editor

Published
2022
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47. Tripartite Motif-Containing 2, a Glutamine Metabolism-Associated Protein, Predicts Poor Patient Outcome in Triple-Negative Breast Cancer Treated with Chemotherapy

Author

Masisi, Brendah K., primary, El Ansari, Rokaya, additional, Alfarsi, Lutfi, additional, Fakroun, Ali, additional, Erkan, Busra, additional, Ibrahim, Asmaa, additional, Toss, Michael, additional, Ellis, Ian O., additional, Rakha, Emad A., additional, and Green, Andrew R., additional

Published
2024
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