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DLAADR 2024 : Deep Learning for Advancing Alzheimer's Disease Research | |||||||||||||||||
Link: https://www.eurekaselect.com/call-for-papers-detail/5223/specialissue | |||||||||||||||||
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Call For Papers | |||||||||||||||||
Journal: Current Alzheimer Research
Guest editor(s): Dr. Yudong Zhang Introduction Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our understanding of AD, enabling early diagnosis, predicting disease progression, and developing innovative therapeutic interventions. Authors are invited to submit their original research or review articles following the submission guidelines of Current Alzheimer Research. All submitted papers will undergo a thorough peer-review process to ensure high scientific quality and relevance to the theme of this thematic issue. Join us in this thematic issue to contribute to the exciting intersection of deep learning and Alzheimer's disease research. Together, we can pave the way for innovative solutions that advance our understanding of AD and improve patient care. Keywords Alzheimer’s disease, deep learning, image analysis, image segmentation, big data, drug discovery, explainable AI Submission: Please email the title of your research to Prof. Yudong Zhang at yudongzhang@ieee.org |
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