Zobrazeno 1 - 10
of 7 070
pro vyhledávání: '"explainable artificial intelligence"'
Publikováno v:
China Finance Review International, 2023, Vol. 14, Issue 3, pp. 522-548.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CFRI-06-2023-0175
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Explainability of convolutional neural networks (CNNs) is integral for their adoption into radiological practice. Commonly used attribution methods localize image areas important for CNN prediction but do not characterize relevant imaging fe
Externí odkaz:
https://doaj.org/article/933854f3e3f34caebec4b7f8fcd1d012
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract This study develops explainable artificial intelligence for predicting safe balance using hospital data, including clinical, neurophysiological, and diffusion tensor imaging properties. Retrospective data from 92 first-time stroke patients f
Externí odkaz:
https://doaj.org/article/85e25663f82649ca8cbb33f1190a7f9a
Autor:
Md. Mahfuz Ahmed, Md. Maruf Hossain, Md. Rakibul Islam, Md. Shahin Ali, Abdullah Al Noman Nafi, Md. Faisal Ahmed, Kazi Mowdud Ahmed, Md. Sipon Miah, Md. Mahbubur Rahman, Mingbo Niu, Md. Khairul Islam
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Brain tumor, a leading cause of uncontrolled cell growth in the central nervous system, presents substantial challenges in medical diagnosis and treatment. Early and accurate detection is essential for effective intervention. This study aims
Externí odkaz:
https://doaj.org/article/057a007074da4c1dadbfc10ef819896f
Publikováno v:
BMC Pregnancy and Childbirth, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Pregnancy termination remains a complex and sensitive issue with approximately 45% of abortions worldwide being unsafe, and 97% of abortions occurring in developing countries. Unsafe pregnancy terminations have implications for women’s rep
Externí odkaz:
https://doaj.org/article/bbe258fa509847d0962052f825b36c72
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 3, Pp 2049-2073 (2024)
Explainable Artificial Intelligence (XAI) is a research area that clarifies AI decision-making processes to build user trust and promote responsible AI. Hence, a key scientific challenge in XAI is the development of methods that generate transparent
Externí odkaz:
https://doaj.org/article/649ade1d712b48b79b5424817e2249d5
Autor:
Shakran Mahmood, Colin Teo, Jeremy Sim, Wei Zhang, Jiang Muyun, R. Bhuvana, Kejia Teo, Tseng Tsai Yeo, Jia Lu, Balazs Gulyas, Cuntai Guan
Publikováno v:
Ibrain, Vol 10, Iss 3, Pp 245-265 (2024)
Abstract The rapid advancement of artificial intelligence (AI) has sparked renewed discussions on its trustworthiness and the concept of eXplainable AI (XAI). Recent research in neuroscience has emphasized the relevance of XAI in studying cognition.
Externí odkaz:
https://doaj.org/article/a0f4a708b0ce48b39e74f7774b86c7a4
Publikováno v:
AI, Vol 5, Iss 3, Pp 1575-1593 (2024)
The rapid development of generative adversarial networks has significantly advanced the generation of synthetic images, presenting valuable opportunities and ethical dilemmas in their potential misuse across various industries. The necessity to disti
Externí odkaz:
https://doaj.org/article/fe0df44d72c54ffa92bb868dff3fbadf
Publikováno v:
Acta Electrotechnica et Informatica, Vol 24, Iss 3, Pp 15-22 (2024)
This paper evaluates the effectiveness of different decoder architectures in enhancing the reconstruction quality of Capsule Neural Networks (CapsNets), which impacts model interpretability. We compared linear, convolutional, and residual decoders to
Externí odkaz:
https://doaj.org/article/f1ae90c0391547dbada636431ed07765
Autor:
Songyang An, David Squirrell
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retina and systemic health. Unlike conventional AI models trained on well-recognized retinal fea
Externí odkaz:
https://doaj.org/article/efa3f44dae414ae092a7f566a18e8d39