Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.

Background: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.

Objective: This study aims to assess and compare medical AI-related attitudes among medical students in general medicine and in one of the visually oriented fields (pathology), along with illuminating their anticipated role of AI in the rapidly evolving landscape of AI-enhanced health care.

Public Perceptions of Surgeon Attire in Saudi Arabia.

Introduction: Surgeon attire significantly affects patients' perceptions and can improve patient-surgeon relationships, which are crucial for patient comfort, experience, satisfaction, and treatment adherence. Understanding patient preferences for surgeon attire is essential, particularly in Saudi Arabia, for establishing appropriate dress codes in healthcare institutions. This national cross-sectional study aimed to fill this gap by assessing patient preferences for surgeon attire and its impact on patients' confidence in their surgeons across various medical settings.

Exploration of BRCA1 and BRCA2 mutations in gastric cancer patients through next generation sequencing: implications for diagnosis and therapy.

Objectives: The study aims to characterize BRCA1/2 mutations in Pakistani gastric cancer (GC) patients, identifying unique pathogenic variants and evaluating their potential as diagnostic biomarkers, while also exploring therapeutic avenues for personalized treatment strategies.

Methodology: In this study, we investigated the role of Breast Cancer gene 1 (BRCA1) and Breast Cancer gene 2 (BRCA2) mutations in Pakistani GC patients and their functional implications using Next-Generation Sequencing (NGS).

Results: Through NGS, we identified a total of 19 mutations in BRCA1 and 11 mutations in BRCA2, all with high mutation quality scores.

Elucidating gastric cancer mechanisms and therapeutic potential of Adociaquinone A targeting EGFR: A genomic analysis and Computer Aided Drug Design (CADD) approach.

Gastric cancer predominantly adenocarcinoma, accounts for over 85% of gastric cancer diagnoses. Current therapeutic options are limited, necessitating the discovery of novel drug targets and effective treatments. The Affymetrix gene expression microarray dataset (GSE64951) was retrieved from NCBI-GEO data normalization and DEGs identification was done by using R-Bioconductor package.