Artificial intelligence (AI) pertains to the ability of computers or computer-controlled machines to perform activities that demand the cognitive function and performance level of the human brain. The use of AI in medicine and health care is growing rapidly, significantly impacting areas such as medical diagnostics, drug development, treatment personalization, supportive health services, genomics, and public health management. AI offers several advantages; however, its rampant rise in health care also raises concerns regarding legal liability, ethics, and data privacy. Technological singularity (TS) is a hypothetical future point in time when AI will surpass human intelligence. If it occurs, TS in health care would imply the replacement of human medical practitioners with AI-guided robots and peripheral systems. Considering the pace at which technological advances are taking place in the arena of AI, and the pace at which AI is being integrated with health care systems, it is not be unreasonable to believe that TS in health care might occur in the near future and that AI-enabled services will profoundly augment the capabilities of doctors, if not completely replace them. There is a need to understand the associated challenges so that we may better prepare the health care system and society to embrace such a change – if it happens.

This perspective paper provides a comprehensive examination of artificial intelligence (AI) in healthcare, focusing on its transformative impact on clinical practices, decision-making, and physician-patient relationships. By integrating insights from evidence, research, and real-world examples, it offers a balanced analysis of AI’s capabilities and limitations, emphasizing its role in streamlining administrative processes, enhancing patient care, and reducing physician burnout while maintaining a human-centric approach in medicine. The research underscores AI’s capacity to augment clinical decision-making and improve patient interactions, but it also highlights the variable impact of AI in different healthcare settings. The need for context-specific adaptations and careful integration of AI technologies into existing healthcare workflows is emphasized to maximize benefits and minimize unintended consequences. Significant attention is given to the implications of AI on the roles and competencies of healthcare professionals. The emergence of AI necessitates new skills in data literacy and technology use, prompting a shift in educational curricula towards digital health and AI training. Ethical considerations are a pivotal aspect of the discussion. The paper explores the challenges posed by data privacy concerns, algorithmic biases, and ensuring equitable access to AI-driven healthcare. It advocates for the development of comprehensive ethical frameworks and ongoing research to guide the responsible use of AI in healthcare. Conclusively, the paper advocates for a balanced approach to AI adoption in healthcare, highlighting the importance of ongoing research, strategic implementation, and the synergistic combination of human expertise with AI technologies for optimal patient care.

An increasing number of people are opting for cosmetic surgeries. For many years, the physical and aesthetic appearance of Caucasians has been considered to be ideal. However, it is now commonly acknowledged that attractiveness and aesthetic standards vary among cultural backgrounds and ethnic groups and that Western attractiveness criteria no longer apply to all. Herein, we conducted a comprehensive review of studies that examined cultural and ethnic variations in preferences for facial, breast, and gluteal aesthetics, as well as reviewed studies that investigated ethnic disparities in attitudes and motivations for cosmetic surgery. A total of 4532 references were identified, 66 of which met the inclusion criteria. Several studies have reported that facial golden ratios are invalid for representing perceived attractiveness standards among different ethnicities. The majority of studies also indicated that facial aesthetic interventions should not aim to Westernize but to optimize ethnic traits. Significant ethnic differences in preferences for upper- and lower-pole breast proportions have been reported. The size of the buttocks and waist-to-hip ratio were identified as the main factors of buttock aesthetics, with buttock size preferences having a high ethnic diversity. Interest in cosmetic surgical procedures while maintaining ethnic identity continues to grow among young women worldwide. This comprehensive review strongly suggests that accommodating cultural and ethnic differences in aesthetic standards in cosmetic surgery planning can lead to more acceptable cosmetic outcomes.

Ideal emitters for organic light-emitting diodes (OLEDs) are capable of efficiently harvesting non-emissive triplet states, have high colour purity, and possess high photoluminescence quantum yields (PLQYs). Maintaining colour purity and PLQY is particularly challenging for multi-carbazole thermally activated delayed fluorescence (TADF) materials that form persistent dimers due to intermolecular interactions of their extended aromatic systems (with altered electronic states). Addressing this challenge, three new emitters are presented, which demonstrate that, somewhat counterintuitively, sterically uncrowded acceptor units can suppress these undesirable interactions. They do so by allowing the surrounding carbazole donors to be arranged with lower dihedral angles, which in turn limits their availability for dimerization. A new pyrazine-centered emitter 4CzPyz is contrasted directly with the cyanopyridine and terephthalonitrile analogs, 4CzCNPy and 4CzTPN respectively. The pyrazine derivative demonstrates enhanced colour stability in the solid-state compared to the cyanopyridine and terephthalonitrile acceptors, which we assign to its absence of intermolecular face-to-face aromatic interactions. This suppression of dimer formation is shared by two cyanopyrazine emitters 2Cz2CNPyz and 3CzCNPyz, each of which feature reduced steric pressure and flatter Cz-Pyz dihedral angles than non-heterocyclic analogues. Flatter dihedral angles consequently lead to C-H bonds of the Cz donors extending outwards at angles that prevent the stacking required for dimerization. This expanded understanding of dimer formation in TADF materials will guide future efforts to maintain colour stability in higher performance TADF materials by curbing the prevalence of face-to-face aromatic interactions.

Several studies have reported elevated serum bilirubin or reduced serum sodium levels in patients with complicated appendicitis (CA). This study examined the efficacy of hyperbilirubinemia, hyponatremia, and both combined in the preoperative diagnosis of CA. Patients who underwent surgery for acute appendicitis were included in this retrospective review. In total, 247 patients were included in the final analysis. Of these, 36 (14.2%) had early appendicitis, 177 (72.0%) had acute suppurative appendicitis, 32 (13.0%) had necrotizing/gangrenous acute appendicitis, and 2 (0.8%) had other types of appendicitis. The mean total bilirubin (TBIL) level was significantly higher in patients with CA than in those with uncomplicated appendicitis. Conversely, the mean serum sodium level was significantly lower in patients with CA than in those with uncomplicated appendicitis. The levels of TBIL (odds ratio: 1.098, 95% CI: 1.052–1.147) and serum sodium (odds ratio: 0.743, 95% CI: 0.646–0.855) were associated with CA. Hyponatremia combined with hyperbilirubinemia yielded significant discriminatory value for the diagnosis of CA. TBIL and serum sodium levels can be considered as adjuvant parameters in the diagnosis of perforated/necrotizing appendicitis. Although hyperbilirubinemia and hyponatremia together were better able to determine the risk of CA than either marker alone, other markers are required to definitively predict CA. Furthermore, large-scale studies are needed to confirm these findings.

Artificial intelligence (AI) is increasingly reshaping cosmetic surgery by enhancing surgical planning, predicting outcomes, and enabling objective aesthetic assessment. Through narrative synthesis of existing literature and case studies, this perspective paper explores the issue of algorithmic bias in AI-powered aesthetic technologies and presents a framework for culturally sensitive application within cosmetic surgery practices in the Middle East and North Africa (MENA) region. Existing AI systems are predominantly trained on datasets that underrepresent MENA phenotypes, resulting in aesthetic recommendations that disproportionately reflect Western beauty ideals. The MENA region, however, encompasses a broad spectrum of beauty standards that merge traditional cultural aesthetics with modern global trends, posing unique challenges for AI integration. To ensure ethical and clinically relevant deployment, AI systems must undergo fundamental changes in algorithm design, including the incorporation of culturally diverse datasets with adequate MENA representation, implementation of cultural competency principles, and active collaboration with regional healthcare professionals. The framework outlines concrete criteria for evaluating cultural representativeness in AI training data and outcome assessments, supporting future empirical validation. Developing culturally aware AI tools is both a moral obligation and a clinical priority. This framework provides both a moral imperative and clinical pathway for ensuring AI serves to support, rather than homogenize, the region’s diverse aesthetic traditions.