The importance of data in the social and behavioral domains to biomedical research is increasing, but ensuring the reusability of such data through standardization is not a trivial task. To start addressing this challenge, we developed a semantic model of the physical activity domain by reviewing 302 physical activity questions collected from standardized questionnaires and public data repositories. Our semantic model is comprised of activity keywords, qualifiers, response measures and context. We identified three types of contexts: active lifestyle, physical capacity, and environment. The majority (94%) of the 204 activity keywords extracted from the 302 questions were mapped to the UMLS Metathesaurus. Preliminary evaluation of our model with 309 additional activity questions showed that the majority of the questions were related to one of the three context categories. We also noted the need to expand context categories to incorporate the questions assessing psychological aspects of dealing with physical activities.
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Psychol Aging
January 2025
Department of Psychology, National Taiwan University.
The Socioemotional Selectivity Theory (SST) posits that older and younger adults have different life goals due to differences in perceived remaining lifetime. Younger adults focus more on future-oriented knowledge exploration and forming new friendships, while older adults prioritize present-focused emotional regulation and maintaining close relationships. While previous research has found these age differences manifest in autobiographical textual expressions, their presence in verbal communication remains unexplored.
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January 2025
Department of Psychology, Western University, London, Canada.
Word norming datasets have become an important resource for psycholinguistic research, and they are based on the underlying assumption that individual differences are inconsequential to the measurement of semantic dimensions. In this pre-registered study we tested this assumption by examining whether individual differences in motor imagery are related to variance in semantic ratings. We collected graspability ratings (i.
View Article and Find Full Text PDFMethodsX
June 2025
Assistant Professor, Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamil Nadu, 600062, India.
Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. Recent advancements in artificial intelligence have introduced new opportunities for enhancing glaucoma detection.
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December 2024
Department of Gastroenterology, Ponderas Academic Hospital, Bucharest, Romania.
Background: EUS-guided fine-needle biopsy is the procedure of choice for the diagnosis of pancreatic ductal adenocarcinoma (PDAC). Nevertheless, the samples obtained are small and require expertise in pathology, whereas the diagnosis is difficult in view of the scarcity of malignant cells and the important desmoplastic reaction of these tumors. With the help of artificial intelligence, the deep learning architectures produce a fast, accurate, and automated approach for PDAC image segmentation based on whole-slide imaging.
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December 2025
Image Processing Laboratory, University of Valencia, Valencia, Spain.
In recent years, substantial strides have been made in the field of visual image reconstruction, particularly in its capacity to generate high-quality visual representations from human brain activity while considering semantic information. This advancement not only enables the recreation of visual content but also provides valuable insights into the intricate processes occurring within high-order functional brain regions, contributing to a deeper understanding of brain function. However, considering fusion semantics in reconstructing visual images from brain activity involves semantic-to-image guide reconstruction and may ignore underlying neural computational mechanisms, which does not represent true reconstruction from brain activity.
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