Download full-text PDF

Source

Publication Analysis

Top Keywords

[what reliable
4
reliable treatment
4
treatment glomerulonephritis?]
4
[what
1
treatment
1
glomerulonephritis?]
1

Similar Publications

In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.

View Article and Find Full Text PDF

Job-exposure matrix (JEM) validity on crystalline silica among systemic sclerosis patients.

Occup Med (Lond)

January 2025

Maine et Loire, Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, IRSET-ESTER, SFR ICAT, CAPTV CDC, 49000 Angers, France.

Background: Systemic sclerosis (SSc) is the connective tissue disease with the highest individual mortality. Crystalline silica is known to be an occupational risk factor for SSc. To assess past crystalline silica exposure, we aimed to study the validity of a job exposure matrix (JEM) to assess occupational exposure to crystalline silica compared to specific occupational interviews in two populations of SSc patients.

View Article and Find Full Text PDF

Transformers for Neuroimage Segmentation: Scoping Review.

J Med Internet Res

January 2025

Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.

Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.

View Article and Find Full Text PDF

Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review.

JMIR Res Protoc

January 2025

Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.

Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.

View Article and Find Full Text PDF

Background: Evaluating digital health service delivery in primary health care requires a validated questionnaire to comprehensively assess users' ability to implement tasks customized to the program's needs.

Objective: This study aimed to develop, test the reliability of, and validate the Tele-Primary Care Oral Health Clinical Information System (TPC-OHCIS) questionnaire for evaluating the implementation of maternal and child digital health information systems.

Methods: A cross-sectional study was conducted in 2 phases.

View Article and Find Full Text PDF

Want 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!