Windsor University School of Medicine is a private offshore medical school located in Cayon, Saint Mary Cayon Parish, Saint Kitts and Nevis in the Caribbean. Windsor confers upon its graduates the Doctor of Medicine (MD) degree. The university also has clinical education campuses in Carbondale, Illinois and Houghton Lake, Michigan. Administrative offices are located in Monee, Illinois.
Rural and underserved communities continue to face barriers to timely and accurate healthcare due to shortages of specialists, limited diagnostic infrastructure, and geographic isolation. Artificial intelligence (AI)-driven diagnostic tools, including machine learning (ML) algorithms, telehealth platforms, and clinical decision support systems, have the potential to address these challenges. A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Scopus, Web of Science, and Embase were searched for studies published between January 2010 and April 2025 that evaluated AI-based diagnostic interventions in rural or low-resource settings. Findings were synthesized thematically to assess diagnostic performance, healthcare access, efficiency, and implementation factors. Twenty-six studies met the inclusion criteria, including observational studies, implementation case reports, and systematic reviews. Overall, AI tools were associated with improved diagnostic accuracy, reduced turnaround times, and enhanced access to services through mobile and telehealth applications. Commonly reported barriers included limited digital infrastructure, gaps in provider training, data privacy concerns, and regulatory uncertainty, while enabling factors included community trust, integration with existing health systems, and supportive policy environments. AI-driven diagnostics therefore show considerable promise for reducing inequities in rural healthcare, although successful implementation will require context-specific strategies, sustained infrastructure investment, and strong ethical and regulatory oversight.
Background and objective:Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that predisposes individuals to multiple organ involvement, with renal complications, particularly lupus nephritis (LN), which is common and clinically significant. The classification and prognosis of LN largely depend on renal biopsy findings, including histopathology, direct immunofluorescence (IF), and electron microscopy. This study aimed to correlate clinicopathological features of SLE patients with LN classes according to the International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification. Methods:This retrospective cohort study was conducted over 5 years and included 65 patients with biopsy-proven LN. Patients were categorized into six histological classes based on the ISN/RPS 2003 classification. Demographic, clinical, laboratory, histopathological, and IF data were collected and correlated. Statistical analysis was performed, and a P-value < 0.05 was considered significant. Results:Anemia was the most frequent hematological abnormality. Class IV LN was the predominant histologic subtype in 56.92% of the cases. Statistically significant associations were found between LN class and serum creatinine level, estimated glomerular filtration rate, proteinuria, and activity index. Interstitial fibrosis and tubular atrophy significantly correlated with elevated serum creatinine levels. Conclusion:This study highlights strong clinicopathological correlations in LN, especially between renal function parameters and histological indices. The integration of routine renal profiles, urine analysis, and histological scoring can guide clinical decision-making and underscore the utility of repeat biopsies during follow-up.
Early-career neurosurgeon training has not yet fully recovered from the decrease in operative exposure that began during the early COVID era. Elective case cancellations, redeployment, and limited staff access to operating rooms reduced the chances of graduated responsibility across a variety of settings and widened existing gaps in the global workforce. Much of this was addressed by numerous programs that reinforced the application of simulation using inexpensive models and virtual environments, helping keep skills developing in the absence of practical experience. It was reported that simulator hours and trainee confidence improved, although practical surgery was needed to consolidate them. Online instruction, video-conferencing dissections, and organized mentoring also assisted learning, particularly in areas where training facilities are not evenly distributed. New interest in digital tools and early uses of artificial intelligence were indicative of a larger project to create flexible training systems. Developing a systematic roadmap that brings together case-log surveillance, simulation, video assessment, stratified mentorship, and partners in networks can help stabilize and modernize early career neurosurgical education.
The global neurosurgical literature is dominated by high-income countries, with low- and middle-income countries (LMICs) contributing minimally despite bearing the most significant share of the neurosurgical disease burden. Underrepresentation limits equitable knowledge dissemination and the relevance of guidelines. The objective of this review was to assess neurosurgical publication disparities, identify deterrents to LMIC participation, and outline initiatives that foster equity and inclusion in research. This narrative review synthesized evidence on global disparities in neurosurgical literature through a structured search of PubMed, Scopus, and Google Scholar (2010-2025). Eligible studies examined research output, authorship trends, publication barriers, or equity initiatives. Findings mapped bibliometric patterns, highlighted structural barriers, and synthesized strategies to promote equitable neurosurgical scholarship. More than two-thirds of neurosurgical reviews come from North America and Europe, whereas less than 10% come from Africa and South-East Asia. Barriers to publication include limited funding, high article processing charges, lack of mentorship, and weak institutional infrastructure. LMIC authors are often relegated to middle authorship, which decreases exposure and hinders academic advancement. Case studies from Africa, South Asia, and Latin America highlight progress in expanding the workforce and in training for specific areas, but persistent research inequities remain. Recent initiatives, such as AuthorAID, HINARI, African Neurosurgical Research Collaborative, and open-access waiver programs, have demonstrated measurable improvements in LMIC research output and authorial independence. Significant inequities persist in neurosurgical research. For sustainable solutions, there is an important need for structural reforms: expanded mentorship, equitable funding, inclusive editorial policies, and strengthened regional collaborations that ensure global neurosurgical research reflects diverse contexts and meaningfully contributes to worldwide patient care.
