Cognition is influenced by a host of factors, including the patient's medical, psychiatric, and developmental history; sociocultural and demographic factors; modifiable behavioral factors; and structural and social determinants of health. Neuropsychological approaches include interpreting test data in the context of these factors to classify impairment and derive a cognitive diagnosis accurately. Failure to integrate an individual's sociodemographic, sociocultural, and developmental background can result in diagnostic errors, which have critical clinical implications for patient care.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ncl.2024.05.004 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The assessment of point-of-care ultrasound (POCUS) in residency: the benefits of a four-year longitudinally integrated curriculum.
J Osteopath Med
January 2025
Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ, USA.
Context: Point-of-care ultrasound (POCUS) has diverse applications across various clinical specialties, serving as an adjunct to clinical findings and as a tool for increasing the quality of patient care. Owing to its multifunctionality, a growing number of medical schools are increasingly incorporating POCUS training into their curriculum, some offering hands-on training during the first 2 years of didactics and others utilizing a longitudinal exposure model integrated into all 4 years of medical school education. Midwestern University Arizona College of Osteopathic Medicine (MWU-AZCOM) adopted a 4-year longitudinal approach to include POCUS education in 2017.
View Article and Find Full Text PDFSTMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model.
Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.
View Article and Find Full Text PDFZhili decoction ameliorates ulcerative colitis by modulating gut microbiota and related metabolite, and inhibiting the TLR4/NF-κB/NLRP3 pathway.
Front Pharmacol
December 2024
Colorectal and Anal Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China.
Ethnopharmacological Importance: Zhili decoction (ZLD) is a traditional Chinese medicine prescription for ulcerative colitis (UC). However, the mechanism by which ZLD exerts its therapeutic effects in the context of UC remains unclear.
Aim Of Study: The aim of this study was to investigate the effects of ZLD on the gut microbiota and related fecal metabolite levels using a mouse model of UC.
Peptide therapeutics, a major class of medicines, have achieved remarkable success across diseases such as diabetes and cancer, with landmark examples such as GLP-1 receptor agonists revolutionizing the treatment of type-2 diabetes and obesity. Despite their success, designing peptides that satisfy multiple conflicting objectives, such as target binding affinity, solubility, and membrane permeability, remains a major challenge. Classical drug development and structure-based design are ineffective for such tasks, as they fail to optimize global functional properties critical for therapeutic efficacy.
View Article and Find Full Text PDFMetal-organic frameworks (MOFs) are porous, crystalline materials with high surface area, adjustable porosity, and structural tunability, making them ideal for diverse applications. However, traditional experimental and computational methods have limited scalability and interpretability, hindering effective exploration of MOF structure-property relationships. To address these challenges, we introduce, for the first time, a category-specific topological learning (CSTL), which combines algebraic topology with chemical insights for robust property prediction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!