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Systematic Review of Hybrid Vision Transformer Architectures for Radiological Image Analysis.
J Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFResponding to: Rethinking Leadership in Academic Medicine: Embracing a Broader Definition of Success : Original article: Sticky Floor, Broken Ladder, and Glass Ceiling in Internal Medicine Academic Ranking, Leadership, and Research Productivity.
J Gen Intern Med
January 2025
Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling.
Acta Pharmacol Sin
January 2025
Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Computational target identification plays a pivotal role in the drug development process. With the significant advancements of deep learning methods for protein structure prediction, the structural coverage of human proteome has increased substantially. This progress inspired the development of the first genome-wide small molecule targets scanning method.
View Article and Find Full Text PDFRanking tasks in recognition memory: A direct test of the two-high-threshold contrast model.
J Exp Psychol Gen
January 2025
Department of Psychology, University of Freiburg.
It has long been debated whether latent memory signals determine recognition judgments directly or through a small number of discrete states. Often, signal detection theory (SDT) models instantiate the former perspective, whereas the two-high-threshold (2HT) model instantiates the latter. Kellen and Klauer (2014) conducted a critical test using a ranking paradigm that yielded results in line with common SDT models and incompatible with the 2HT model.
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