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Effectiveness of information technology-based cognitive behavioral therapy on depression and anxiety symptoms among older adults: Systematic review and meta-analysis.
Gen Hosp Psychiatry
December 2024
School of Basic Medical Sciences, Hubei University of Chinese Medicine, Wuhan 430061, China; Department of Geriatrics, Hubei Provincial Hospital of Traditional Chinese Medicine (Affiliated Hospital of Hubei University of Chinese Medicine), Wuhan 430060, China. Electronic address:
Background: Depression and anxiety are prevalent among older adults. However, most older adults have poor access to age-specific mental health services. While Information technology-based Cognitive Behavioral Therapy (ICBT) has shown promise as an accessible alternative to face-to-face interventions, its effectiveness specifically within the older adults warrants further investigation.
View Article and Find Full Text PDFChanges in traffic-related air pollution exposures and associations with adverse birth outcomes over 20 years in Texas.
Int J Epidemiol
December 2024
School of Nutrition and Public Health, College of Health, Oregon State University, Corvallis, OR, USA.
Background: Billions of dollars have been spent implementing regulations to reduce traffic-related air pollution (TRAP) from exhaust pipe emissions. However, few health studies have evaluated the change in TRAP emissions and associations with infant health outcomes. We hypothesize that the magnitude of association between vehicle exposure measures and adverse birth outcomes has decreased over time, parallelling regulatory improvements in exhaust pipe emissions.
View Article and Find Full Text PDFEvaluation of Retinal Capillary Density using OCT Angiography according to Acute Ischemic Stroke Etiologies - A Matched Case -Control Study.
Retina
January 2025
Neuroradiology Department, CHRU Gui de Chauliac, F-34091 Montpellier, France.
Purpose: To investigate retinal microvascular changes in ischemic stroke patients using optical coherence tomography angiography (OCT-A) and assess these alterations based on stroke etiology.
Methods: Case-control study conducted at Montpellier University Hospital from May 2021 to March 2022 (IRB: 202000607). Retinal vascular features were compared between strokes patients and age- and sex- matched controls.
Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Using Medical Text.
JMIR Med Inform
January 2025
Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China.
Background: Machine learning models can reduce the burden on doctors by converting medical records into International Classification of Diseases (ICD) codes in real time, thereby enhancing the efficiency of diagnosis and treatment. However, it faces challenges such as small datasets, diverse writing styles, unstructured records, and the need for semimanual preprocessing. Existing approaches, such as naive Bayes, Word2Vec, and convolutional neural networks, have limitations in handling missing values and understanding the context of medical texts, leading to a high error rate.
View Article and Find Full Text PDFTwo-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study.
J Med Internet Res
January 2025
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
Background: The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However, due to the large volume of data, obtaining useful insights through natural language processing technologies such as large language models is challenging.
Objective: This paper aims to develop a retrieval-augmented generation (RAG) architecture for medical question answering pertaining to clinicians' queries on emerging issues associated with health-related topics, using user-generated medical information on social media.
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