The power of Artificial Intelligence (AI) combined with the surgeons’ expertise leads to breakthroughs in surgical care, bringing new hope to patients. Utilizing deep learning-based computer vision techniques in surgical procedures will enhance the healthcare industry. Laparoscopic surgery holds excellent potential for computer vision due to the abundance of real-time laparoscopic recordings captured by digital cameras containing significant unexplored information. Furthermore, with computing power resources becoming increasingly accessible and Machine Learning methods expanding across various industries, the potential for AI in healthcare is vast. There are several objectives of AI’s contribution to laparoscopic surgery; one is an image guidance system to identify anatomical structures in real-time. However, few studies are concerned with intraoperative anatomy recognition in laparoscopic surgery. This study provides a comprehensive review of the current state-of-the-art semantic segmentation techniques, which can guide surgeons during laparoscopic procedures by identifying specific anatomical structures for dissection or avoiding hazardous areas. This review aims to enhance research in AI for surgery to guide innovations towards more successful experiments that can be applied in real-world clinical settings. This AI contribution could revolutionize the field of laparoscopic surgery and improve patient outcomes.

This study aims to determine the extent to which talent identification is implemented in talent management. A Systematic Literature Review (SLR) was conducted to summarize the application of talent identification in the last six years. Researchers use Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to process scientific articles. The literature reveals that while topics related to talent management garner significant attention, research on talent identification within talent management remains relatively scarce despite a gradual increase each year. We compared documents indexed by Scopus Q1 and Q2. The results show that the United States accounted for a significant portion of research on talent identification, representing 16% of the total existing research. Researchers have conducted extensive studies on the medical and pharmaceutical sectors, public services, tourism, and hospitality. The number of citations varied greatly from 1 to 93, with a median value of 20. These studies have also used various research methods with different theoretical bases and produced different analyses. This finding enriches the perspective of talent identification.

Tourist visits to a destination or attraction as a result of the destination being featured on television, video, or the cinema screen were the ones, that stimulated the creation and development of film tourism, which quickly established itself in global conditions. The main objective of the paper was focused on the identification and the perception of the conditions of film tourism development in Slovak republic. So far, a lot of film production has been realized in the country, but this potential has not yet been properly used for the creation of tourism products. Implementation of the study from a methodological point of view took place using several research methods. The pilot scientific abstraction of the issue was followed by the analysis of film conditions in the territory of Slovak Republic and their categorization. The given starting points were followed by the implementation of questionnaire research, the results of which were verified using several research methods such as Doornik-Hansen test, Kruskal-Wallis test. The results of the questionnaire research show a significant positive perception of the potential of filmmaking as a significant factor in the creation of new tourism products. At the same time, they identify key destinations that could potentially become objects of product realization. Due to the fact that this issue has not received adequate attention in domestic conditions, the study brings a new, more comprehensive view of the topic and emphasizes the power of the potential for further development.

The research aimed to: 1) analyze components and indicators of digital transformation leadership among school administrators, 2) assess their leadership needs, and 3) develop mechanism models to promote this leadership. A mixed-method approach was applied, involving three sample groups: 8 experts, 406 administrators, and 7 experts. Data collection tools included semi-structured interviews, leadership scales, needs assessments, and focus group discussions, with analysis performed through construct validity testing, needs assessment, and content analysis. The findings revealed: 1) The components and indicators of digital transformation leadership showed structural validity, as confirmed by the model's alignment with empirical data (Chi-Square = 82.3, df = 65, p = 0.072, CFI = 0.998, TLI = 0.997, RMR = 0.00965, RMSEA = 0.0256). 2) Among the leadership components, "innovative knowledge" ranked highest in need (PNImodified = 0.075), followed by "ideological influence" (0.066), "consideration of individuality" (0.055), "intellectual stimulation" (0.052), and "inspiration" (0.053). 3) Mechanism models for promoting leadership emphasized enhancing these five components to strengthen administrators' skills in applying technology, managing teaching and development plans, and fostering innovation. Administrators were encouraged to tailor strategies to individual needs, inspire personnel, and create a commitment to organizational change and development. These mechanisms aim to equip administrators to effectively lead transformations, motivate staff, and drive educational institutions to adapt and thrive in evolving environments.

In an era of intensified market competition, internal brand management (IBM) has emerged as a critical strategy for aligning employee behavior with brand values. This study investigates how IBM influences brand citizenship behavior (BCB) among front-line restaurant employees in Macao, emphasizing the mediating role of brand identification (BI) and simultaneously testing the moderating effect of leader-member exchange (LMX). Drawing from Social Identity Theory and Social Exchange Theory, the structural equation modeling (SEM) was used to test the model using data from 315 employees across 11 Macao restaurant companies. Analyzing via software package Smart-Pls 4.1, we found that IBM significantly enhances BI, which in turn strongly predicts BCB. While IBM directly impacts BCB, the effect is mediated by BI. Furthermore, LMX moderates the IBM-BI relationships, underscoring the role of leadership in internal branding effectiveness. These findings contribute to the internal branding literature by validating BI as a key psychological mechanism and LMX as a boundary condition. Practically, the study provides insights for restaurant industry seeking to foster brand-aligned behaviors through internal brand management.