Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635492 | PMC |
| http://dx.doi.org/10.3389/fpsyg.2023.1286327 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Searching for new drugs to treat Alzheimer's disease dementia through multiple pathways.
World J Clin Cases
January 2025
Department of Neurology, Guizhou Medical University, Guiyang 550004, Guizhou Province, China.
Dementia is a group of diseases, including Alzheimer's disease (AD), vascular dementia, Lewy body dementia, frontotemporal dementia, Parkinson's disease dementia, metabolic dementia and toxic dementia. The treatment of dementia mainly includes symptomatic treatment by controlling the primary disease and accompanying symptoms, nutritional support therapy for repairing nerve cells, psychological auxiliary treatment, and treatment that improves cognitive function through drugs. Among them, drug therapy to improve cognitive function is important.
View Article and Find Full Text PDFInsights Into Submissions and Medical Journal Publications in Korea.
J Korean Med Sci
January 2025
Division of Infectious Diseases, Department of Internal Medicine, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
We analyzed the publication and submission statuses of Korean medical journals from 2010 to 2024, amidst challenges impacting researchers. Data from 58 domestic journals identified through the 2023 JCR database were used to assess publication status, while data from the () were utilized to examine submission status. The proportion of published original articles by domestic authors decreased by 3% in 2024 compared to 2023.
View Article and Find Full Text PDFTransforming precision medicine: The potential of the clinical artificial intelligent single-cell framework.
Clin Transl Med
January 2025
Department of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.
The editorial, "Clinical and translational mode of single-cell measurements: An artificial intelligent single-cell," introduces the innovative clinical artificial intelligence single-cell (caiSC) system, which merges AI with single-cell informatics to advance real-time diagnostics, disease monitoring, and treatment prediction. By combining clinical data and multimodal molecular inputs, caiSC facilitates personalized medicine, promising enhanced diagnostic precision and tailored therapeutic approaches. Despite its potential, caiSC lacks comprehensive data coverage across cell types and diseases, presenting challenges in data quality and model robustness.
View Article and Find Full Text PDFPromoting Physical Activity in People With Parkinson's Disease Through a Smartphone App: A Pilot Study.
J Neurol Phys Ther
January 2025
Center of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Gelderland, the Netherlands (S.S., N.M.V., S.K.L.D., B.R.B.); Harvard Medical School, Boston, Massachusetts (A.A., M.A.S., E.A.M.); Departments of Epidemiology and Nutrition, T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts (A.A.); Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts (M.A.S., E.A.M.); Mass General Institute for Neurodegenerative Disease, Massachusetts General Hospital, Boston, Massachusetts (M.A.S.); and Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts (E.A.M.).
Background And Purpose: Physical activity has beneficial symptomatic effects for people with Parkinson's disease (PD), but increasing-and sustaining-a physically active lifestyle remains challenging. We investigated the feasibility (ability to increase step counts) and usability of a behavioral intervention using a motivational smartphone application to remotely increase physical activity in PD.
Methods: We performed a 4-week, double-blind pilot trial.
Aim: Lymph node metastasis is an adverse prognostic factor in pancreatic ductal adenocarcinoma. However, it remains a challenge to predict lymph node metastasis using preoperative imaging alone. We used machine learning (combining preoperative imaging findings, tumor markers, and clinical information) to create a novel prediction model for lymph node metastasis in resectable pancreatic ductal adenocarcinoma.
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!