Zobrazeno 1 - 10
of 409
pro vyhledávání: '"Muhammad, Naseer"'
Publikováno v:
Chinese Management Studies, 2024, Vol. 19, Issue 1, pp. 99-115.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CMS-02-2023-0086
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Plant extracts are actively being used worldwide due to the presence of biologically active constituents helping in the preservation of food, and to aid against various diseases owing to their antimicrobial and antioxidant potential. The pre
Externí odkaz:
https://doaj.org/article/77abb6ee95a54870950112101d8000c7
Publikováno v:
BMC Complementary Medicine and Therapies, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Methanolic and chloroformic extract of Achillea millefolium and Chaerophyllum villosum were evaluated for HPLC analysis, genotoxic and antioxidant potential. Materials and methods Genotoxic activity was carried out on human blood
Externí odkaz:
https://doaj.org/article/5e91f91b16fc4f7fa507d38a20b61dc5
Autor:
Lucieri, Adriano, Bajwa, Muhammad Naseer, Braun, Stephan Alexander, Malik, Muhammad Imran, Dengel, Andreas, Ahmed, Sheraz
One principal impediment in the successful deployment of AI-based Computer-Aided Diagnosis (CAD) systems in clinical workflows is their lack of transparent decision making. Although commonly used eXplainable AI methods provide some insight into opaqu
Externí odkaz:
http://arxiv.org/abs/2201.01249
Publikováno v:
Borsa Istanbul Review, Vol 24, Iss 1, Pp 106-117 (2024)
This study investigates how a firm's climate change risk (FCCR) and financial flexibility (FIFL) affect its value and environmental, social, and governance (ESG) performance. We use data from publicly listed US firms for 2012–2021. We employed four
Externí odkaz:
https://doaj.org/article/29e36275490d41a69dcd6cb2a3843212
Remarkable success of modern image-based AI methods and the resulting interest in their applications in critical decision-making processes has led to a surge in efforts to make such intelligent systems transparent and explainable. The need for explai
Externí odkaz:
http://arxiv.org/abs/2011.13169
Autor:
Bajwa, Muhammad Naseer, Singh, Gur Amrit Pal, Neumeier, Wolfgang, Malik, Muhammad Imran, Dengel, Andreas, Ahmed, Sheraz
Scarcity of large publicly available retinal fundus image datasets for automated glaucoma detection has been the bottleneck for successful application of artificial intelligence towards practical Computer-Aided Diagnosis (CAD). A few small datasets t
Externí odkaz:
http://arxiv.org/abs/2006.09158
Autor:
Bajwa, Muhammad Naseer, Taniguchi, Yoshinobu, Malik, Muhammad Imran, Neumeier, Wolfgang, Dengel, Andreas, Ahmed, Sheraz
Visual artefacts of early diabetic retinopathy in retinal fundus images are usually small in size, inconspicuous, and scattered all over retina. Detecting diabetic retinopathy requires physicians to look at the whole image and fixate on some specific
Externí odkaz:
http://arxiv.org/abs/2005.14308
Autor:
Bajwa, Muhammad Naseer, Malik, Muhammad Imran, Siddiqui, Shoaib Ahmed, Dengel, Andreas, Shafait, Faisal, Neumeier, Wolfgang, Ahmed, Sheraz
Publikováno v:
BMC medical informatics and decision making 19.1 (2019): 136
With the advancement of powerful image processing and machine learning techniques, CAD has become ever more prevalent in all fields of medicine including ophthalmology. Since optic disc is the most important part of retinal fundus image for glaucoma
Externí odkaz:
http://arxiv.org/abs/2005.14284
Autor:
Lucieri, Adriano, Bajwa, Muhammad Naseer, Braun, Stephan Alexander, Malik, Muhammad Imran, Dengel, Andreas, Ahmed, Sheraz
Publikováno v:
2020 International Joint Conference on Neural Networks (IJCNN)
Deep learning based medical image classifiers have shown remarkable prowess in various application areas like ophthalmology, dermatology, pathology, and radiology. However, the acceptance of these Computer-Aided Diagnosis (CAD) systems in real clinic
Externí odkaz:
http://arxiv.org/abs/2005.02000