Tuberculosis (TB) is a major cause of deaths by a single infectious agent and has now been a global public health problem due to increasing numbers of drug-resistant cases. Early and effective treatment is crucial to prevent the emergence of drug-resistance strains. This demands the availability of fast and reliable point-of-care (POC) diagnostic methods for effective case management. Commonly used methods to screen and diagnose TB are clinical, immunological, microscopy, radiography, and bacterial culture. In addition, recent advances in molecular diagnostic methods including MTBDRplus, loop-mediated isothermal amplification (LAMP), line probe assay (LPA), GeneXpert, and whole genome sequencing (WGS) have been employed to diagnose and characterize TB. These methods can simultaneously identify Mycobacterium tuberculosis (MTB) and mutation(s) associated with routinely used anti-TB drugs. Here, we review the use of currently available diagnostic methods and strategies including conventional to recently implemented next-generation sequencing (NGS) methods used to detect MTB in clinical perspective.
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http://dx.doi.org/10.1007/s11033-020-05413-7 | DOI Listing |
Appl Neuropsychol Adult
January 2025
Faculty Xavier Institute of Engineering, Mahim, India.
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 PDFJ Clin Endocrinol Metab
January 2025
Department of Internal Medicine and Therapeutics, University of Pavia, 27100 Pavia, Italy.
Background: Thyroid nodules classified cytologically as low-risk indeterminate lesions (TIR3A) on fine-needle aspiration biopsy (FNAB) present a clinical challenge due to their uncertain malignancy risk. This single-center study aimed to evaluate the natural history of TIR3A nodules.
Materials And Methods: FNABs performed between July 2017 and December 2019 were retrospectively retrieved and patients with TIR3A nodules were evaluated at baseline and throughout a follow-up based on ultrasound (US) parameters and clinical data.
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 PDFJ Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
J Med Internet Res
January 2025
Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, China.
This study provides preliminary evidence for real-time functional magnetic resonance imaging neurofeedback (rt-fMRI NF) as a potential intervention approach for internet gaming disorder (IGD). In a preregistered, randomized, single-blind trial, young individuals with elevated IGD risk were trained to downregulate gaming addiction-related brain activity. We show that, after 2 sessions of neurofeedback training, participants successfully downregulated their brain responses to gaming cues, suggesting the therapeutic potential of rt-fMRI NF for IGD (Trial Registration: ClinicalTrials.
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