The Impact of Artificial Intelligence on Healthcare: A Comprehensive Review of Advancements in Diagnostics, Treatment, and Operational Efficiency.

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.

Rituximab Safety Profile: A Seven-Year Retrospective Analysis From Southern India.

Objective: This study aimed to analyze the pattern, severity, and outcomes of adverse drug reactions (ADRs) associated with rituximab use reported to a regional pharmacovigilance center in Kerala, India.

Methods: This retrospective study analyzed rituximab-associated ADRs reported from 2017 to 2023. ADRs were assessed using the WHO-UMC criteria for causality and the Modified Hartwig Siegel Scale for severity.

A Bibliometric Analysis of the Top 100 Cited Qualitative Research Papers in Dentistry From Scopus (1998-2024).

This bibliometric analysis aimed to identify trends among the top 100 most cited qualitative research articles in dentistry. Articles were retrieved from the Scopus database and screened based on predefined inclusion and exclusion criteria. The final set of 100 articles was then analyzed in R Studio (RStudio Team, Boston, MA) to assess performance metrics, including publication and citation trends, citation-publication relationships, and science mapping.