Zobrazeno 1 - 10 of 233 pro vyhledávání: '"Urrehman A"'
1
Akademický článek
Neighborhood attention transformer multiple instance learning for whole slide image classification
Autor: Rukhma Aftab, Qiang Yan, Juanjuan Zhao, Gao Yong, Yue Huajie, Zia Urrehman, Faizi Mohammad Khalid
Publikováno v: Frontiers in Oncology, Vol 14 (2024)
IntroductionPathologists rely on whole slide images (WSIs) to diagnose cancer by identifying tumor cells and subtypes. Deep learning models, particularly weakly supervised ones, classify WSIs using image tiles but may overlook false positives and neg
Externí odkaz: https://doaj.org/article/3a0f00d608504b21a5e51bd6d9d1b891
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4
Akademický článek
Effective lung nodule detection using deep CNN with dual attention mechanisms
Autor: Zia UrRehman, Yan Qiang, Long Wang, Yiwei Shi, Qianqian Yang, Saeed Ullah Khattak, Rukhma Aftab, Juanjuan Zhao
Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Novel methods are required to enhance lung cancer detection, which has overtaken other cancer-related causes of death as the major cause of cancer-related mortality. Radiologists have long-standing methods for locating lung nodules in patien
Externí odkaz: https://doaj.org/article/b46afe0cecc745358413e4abdf803ddb
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8
Akademický článek
Tuning of end-groups in diketopyrrolopyrrole-based acceptors molecules for organic photovoltaics
Autor: Shafiq UrRehman, Hammad Aslam, Shamsa Bibi, Nazish Jahan, Muhammad Irfan Majeed, Haq Nawaz, Samreen Gul Khan, Hong-Xing Zhang
Publikováno v: Sustainable Chemistry for the Environment, Vol 5, Iss , Pp 100068- (2024)
In this computational approach, four small novel acceptor molecules of A2-D-A1-D-A2 type have been designed (S1-S4) by the replacement of terminal acceptor groups (A2) of R molecule with four different types of electron accepting-units. The photovolt
Externí odkaz: https://doaj.org/article/87c6c88969e741788b02ecca2d631b8f
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9
Akademický článek
Graph Neural Network for representation learning of lung cancer
Autor: Rukhma Aftab, Yan Qiang, Juanjuan Zhao, Zia Urrehman, Zijuan Zhao
Publikováno v: BMC Cancer, Vol 23, Iss 1, Pp 1-11 (2023)
Abstract The emergence of image-based systems to improve diagnostic pathology precision, involving the intent to label sets or bags of instances, greatly hinges on Multiple Instance Learning for Whole Slide Images(WSIs). Contemporary works have shown
Externí odkaz: https://doaj.org/article/856e5b938c2747348168b2cf0330f903
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