Publications by authors named "R L Sah"
Background And Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment.
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- The study focused on analyzing multidrug-resistant (MDR) isolates for their ability to form biofilms and the presence of associated genes at a hospital in Nepal.
- A significant majority of the isolates were found to be strong biofilm producers, with 195 out of 200 being MDR and 192 capable of biofilm formation.
- Cinnamaldehyde was the most effective compound in inhibiting biofilm formation, with essential oils and Tween 80 also showing high efficacy, providing insights for potential treatment options against these resistant strains.
Background: Atrial fibrillation (AF) is the most prevalent form of sustained cardiac arrhythmia, with vascular endothelial growth factor (VEGF) increasingly recognized for its potential role in the pathogenesis of AF through mechanisms involving atrial remodeling, inflammation, and fibrosis. This systematic review aims to synthesize available evidence on the association between VEGF and AF, exploring the implications of VEGF as a biomarker and therapeutic target.
Methods: We conducted a comprehensive search across PubMed, Embase, and Web of Science until November 10 2024, selecting studies based on pre-defined criteria that involve adults with AF and measurements of VEGF levels.