# Special Issue on eHealth Innovative Approaches and Applications
###### Abstract  
Innovative ICT technologies, approaches and applications are becoming increasingly pervasive in several domains, including in medicine and healthcare. In these latter cases, physicians and medical professionals can recently incorporated complex and advanced systems, based on the latest technologies, into their daily routines. Scientific research constantly proposes new approaches and applications with high potential for usage in the eHealth sector. For example, the advent of digitised images in pathology and advances in Artificial Intelligence (AI) have led to an explosion of innovation in the traditional field of pathology, creating what is now described as Computational Pathology [1], which defines new and increasingly effective AI approaches for digital image analysis. Similarly, the pervasive adoption of AI in other medical fields has allowed the definition and implementation of innovative systems to support the work of physicians, medical professionals and policy makers, such as recommender systems [2], smart patient support and remote monitoring systems [3, 4]. Another technology that has become increasingly pervasive in medicine in recent years is the Internet of Medical Things (IoMT), which is currently largely adopted in healthcare; this technology is redefining smart healthcare systems and approaches to providing care [5]. Furthermore, the great recent improvements in the field of Natural Language Processing (NLP), with the release of Large Language Models (LLMs) such as ChatGPT, also impacted the biomedical domain, quickly leading to the widespread use of these models in medical research (as in other domains) or in healthcare. Recently, LLMs have provided functional eHealth applications ranging from the development of virtual medical assistants to the acceleration of various benchmarks of several biomedical information tasks, including document classification or relation extraction, exploiting closed-domain models such as BioBERT [6], or BERTMeSH [7]. Examples of further innovative eHealth technologies based on LLMs are smart assistants and question-answering systems, such as Med-PaLM 2 [8], ChatDoctor [9] or MedPrompt [10], which obtain very promising performances and results. On the other hand, this current revolution in the medical domain, thanks to these new technologies and approaches, has some drawbacks and issues that must be taken into account in order to effectively exploit all its advantages without any risks or problems. eHealth approaches must guarantee the required levels of privacy and security [11, 12, 13] during the processing, transmission and sharing of medical and personal information, preventing violations or thefts of patients' sensitive medical data. The scarcity of medical and clinical datasets with high-quality annotations is also a limitation in the development and improvement of innovative eHealth approaches [14, 15, 16]. Furthermore, the increasing number of connected medical devices and the complex digital healthcare delivery systems cause several cyber security issues [17, 18], due to the increased risk of surface attack. Thus, defining innovative cyber security techniques specifically tailored for the healthcare domain is required. The growing volume of medical data, and their complexity and heterogeneity, pose additional challenges for the effective extraction of valuable insights [19, 20, 21]. Inthis case, tailored approaches are also required [22; 23]. Moreover, physician, medical professional and patient awareness must be increased, and all parties must be warned of the possibilities and threats inherent to digital medicine [24; 25]. In this scenario, it becomes crucial to disseminate the most recent results and enhancements achieved by research in the domain of eHealth.