## 3 Results
### Security and Intelligent Platforms: AI as a Driver or Change in Healthcare
For example, the federated learning model in Italy for brain tumor segmentation [86] has not only improved effectiveness but also laid the foundation for new skills needed by healthcare professionals. The \"DeepBlockShield\" [88] represents a qualitative leap in healthcare data security, employing blockchain to effectively protect clinical data, especially those from the deep web. Developed in South Korea, this model establishes new standards in data protection in the healthcare sector, underscoring the growing importance of data security in the digital era. Looking to the future, the expected evolution of intelligent platforms and AI in healthcare includes the development of advanced AI systems and the integration of these technologies into new clinical areas. These studies represent a body of work that not only documents the innovative use of AI and intelligent platforms but also lays the groundwork for their future use in more complex care scenarios, enhancing the resilience and effectiveness of healthcare systems [89; 90; 91]. The increasing use of AI and big data in the healthcare sector not only testifies to their crucial role in healthcare management but also highlights the limitless potential that awaits when technology and human ingenuity work together for the common good. Artificial Intelligence and Resource Management in Healthcare: Towards a Smart and Sustainable Future  
Artificial intelligence (AI) emerges as a true force of change, shaping the future of healthcare systems by endowing them not only with greater intelligence but also with remarkable sensitivity to individual needs. The innovations within these systems, guided by a data-driven multimodal approach, have been meticulously documented in Table 6.  
These solutions, ranging from disease analysis to diagnosis and treatment, underscore the crucial importance of effective data management and improved decision-making processes [92]. This evolution has been inspired by the rapid development of AI-based medical services, which are radically transforming healthcare delivery. In this rapidly evolving context, the study by [PERSON] et al. (2022) represents a further advancement, exploring the use of artificial intelligence to optimize resource management in the healthcare sector [93]. The management of healthcare information is currently at a critical juncture, with the need to integrate numerous independent applications into more cohesive and reliable systems [94]. This demand for coherence and quality in healthcare information systems is driving innovative solutions that can significantly enhance the efficiency and dependability of intelligent healthcare systems. Simultaneously, the study by [PERSON] (2023) makes a significant contribution by investigating the impact of AI on treatment personalization and patient management, highlighting how AI can facilitate more accurate diagnoses and tailored treatments [95]. However, a critical element for the success of efficient and intelligent healthcare systems is trust in AI. Despite the sometimes-human-like performance of AI models, their perception as \"black boxes\" limits practical application, especially in the healthcare field. This is where explainable artificial intelligence (XAI) comes into play [96]. XAI provides transparency in model predictions and encourages the use of AI systems in the healthcare sector, paving the way for the development of holistic systems for smart cities. Furthermore, the study by [PERSON] et al. (2022) offers an innovative perspective on the use of AI to enhance patient safety and risk management, demonstrating how AI-based decision support systems can identify potential risks in real time [97]. Each research endeavor in this field contributes to a broader narrative, showcasing not only the evolution of healthcare in the digital age but also anticipating the future of the sector.