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Explainable deep learning framework incorporating medical knowledge for insulin titration in diabetes - Communications Medicine
Abstract Deep learning has shown promise in diabetes management but faces challenges in real-world application due to its “black-box” nature, characterized by opaque internal decision-making processes. Explainable artificial intelligence (XAI) methods have been proposed to enhance model transparency. However, most of current XAI methods applied in the medical field often ignore the interaction of features in complex environments and pose deviation from clinical domain knowledge.
Antifungal Pseuboyenes A-J, Bergamotene-Derived Sesquiterpenoids from a Cold-Seep-Derived Pseudallescheria boydii
Zhen Ying CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Nanhai Road 7, Qingdao 266071, People’s Republic of China University of Chinese Academy of Sciences, Yuquan Road 19A, Beijing 100049, People’s Republic of China , Xiao-Ming Li CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of...
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