AI Article Synopsis

  • Tuberculosis (TB) is a significant global health issue, primarily due to rising drug-resistant cases, making early, effective treatment essential.
  • Reliable point-of-care diagnostic methods are crucial for managing TB effectively, with common techniques including clinical assessments, microscopy, and culture, alongside newer molecular methods like GeneXpert and whole genome sequencing.
  • This review focuses on various diagnostic strategies, from traditional methods to advanced next-generation sequencing, aimed at detecting Mycobacterium tuberculosis and resistance mutations in a clinical context.

Article Abstract

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.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11033-020-05413-7DOI Listing

Publication Analysis

Top Keywords

diagnostic methods
12
mycobacterium tuberculosis
8
methods
6
advances diagnosis
4
tuberculosis
4
diagnosis tuberculosis
4
tuberculosis update
4
update molecular
4
molecular diagnosis
4
diagnosis mycobacterium
4

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

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.

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

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.

View Article and Find Full Text PDF

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.

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!