ISMICT 2025

This talk will provide insights on how edge computing can support and enhance a few healthcare applications by enabling real-time data processing. In particular, I will first introduce LiveMicro, an edge-based system that enables pathologists to control a microscope in real-time. By offloading computations for tasks like nuclei detection and tumor margin assessment to nearby servers, pathologists can rapidly cooperate on a diagnosis, and seek consultations for continuing medical education and training, without the overhead of sending entire datasets to the cloud. LiveMicro provides the ability to jointly control the microscope's stage, zoom, and pan, a crucial ability when performing a pathology diagnosis. Second, I will discuss EdgeEcho, an architecture that offloads echo stream processing to edge nodes. Here, optimized data structures like Cuckoo filters handle complex membership queries quickly, boosting real-time analysis of heart volume and function. Collectively, these examples illustrate how edge computing can expedite diagnoses, facilitate collaboration, and ultimately improve patient outcomes in resource-intensive clinical environments.

Flavio Esposito is an Associate Professor of Computer Science, Graduate Coordinator, and a Fellow of the Research Institute at Saint Louis University (SLU), in St.Louis, MO (USA). He received his Ph.D. in Computer Science at Boston University in 2013, and his MS in Telecommunication Engineering from the University of Florence, Italy. Before joining SLU, Flavio was a senior software engineer in high-frequency trading and worked at Bell Laboratories, NJ, and Raytheon BBN Technologies, in Cambridge, MA. Most of Flavio’s current research centers on cyber-physical and cyber-human systems, (wireless) networked systems, and AI/ML applied to precision agriculture and healthcare. Flavio is also the CEO and co-founder of Spaghetti Code Labs, LLC, a profitable company that focuses on cybersecurity and privacy education.

Traditional healthcare systems cannot satisfy anymore the needs of a continuously growing and developing society. The world today needs to face problems such as the aging of population and the inherent need of assisted-living environments for elderly people. The 5G network and prospective 6G solutions along with the pervasiveness of IoT devices will provide unprecedented benefits and innovations in several areas such as data science, machine learning and signal processing which are expected to boost the digital transformation of healthcare. This keynote includes the following main goals: i) to discuss the impact of future networks on the latest eHealth advancements by presenting innovative and efficient solutions; ii) to illustrate the aspects of applying future networks in healthcare systems by showing some practical applications and the response to technology-assisted medical care and treatments; iii) to provide further directions for research posing new problems and challenges in the eHealth field.

Andrea Sciarrone is Associate Professor in the research staff of the Telecommunication Group and, of the Digital Signal Processing (DSP) Laboratory at the DITEN department of the University of Genoa.
He has been the Chair of the IEEE ComSoc e-Health TC and he's currently Secretary of the IEEE Italy Chapter. Furthermore, he has been involved in several funded e-health projects, both national and international. He is author of more than 80 scientific pubblications. In 2016, the IEEE Communication Society presents him the best paper award during the International Conference on Cloud Networking in Pisa, Italy.
He is also the Department reference person for the PNRR RAISE Ecosystem on "Smart Devices and Technologies for Personal and Remote Healthcare". His research interests include signal processing over Internet of Things, context awareness and eHealth applications.

The emotional dimension is nowadays attracting the interest of the research in many different fields. The individual behavior during everyday life, as well as during specific tasks (work, rehabilitation; etc.) seems to be highly determined by the emotional state. Similarly, a strong correlation was demonstrated between the emotional state (i.e. stress) and the risk of developing some pathologies, among the others psychiatric, neurologic, cardiac. Emotions have been traditionally described from a qualitative point of view, on the other hand, they are responsible for well define physiological responses. For this reason the interest is now growing on the measurement and quantification of the emotional state through features obtained from non-invasive physiological data. Several physiological signals are commonly used to detect emotions: heart rate and heart rate variability; electrodermal activity and galvanic skin response; electroencephalography and event related responses; respiration and body temperature. Similarly, different processing pipelines have been proposed for the extraction of relevant features and their correct classification. Here we want to discuss the relevant issues related to the methodologies that are applied for emotion detection and quantification, including the sensors, the signals and the features of interest, the classification strategies, the main fields of application and the open challenges for the future directions.

Anna M. Bianchi is full professor of Biomedical Engineering at the Department of Electronics, Information and Bioengineering of the Polytechnic University of Milan.
She graduated in Electronic Engineering at the Polytechnic University of Milan and between 1987 and 2000 she was a researcher at the Laboratory of Biomedical Engineering of the IRCCS Ospedale S. Raffaele in Milan; in 2001 she joined the Department of Bioengineering of the Polytechnic University of Milan.
Her teaching activities concern Biomedical Signal Processing (Bachelor's Degree) and Medical Informatics (Master's Degree). She is also a teacher in the PhD courses in Bioengineering and since 2004 she has been a member of the teaching staff of the same PhD program. She is author of more than 100 papers published in international journals (h-index = 26), she collaborated in several research projects funded by the European Community EU (MyHeart, HeartCycle, Neuropt) and she was Unit coordinator in the EU projects Psyche (FP7), Pickfiler (FP7), and she is currently Unit coordinator of the EU project LINK (H2020).
She is a member of IEEE-Engineering in Medicine and Biology Society, and member of the technical committees on Cardiopulmonary Systems and on Neuroengineering. Since 2012 she is a fellow of EAMBES (European Alliance for Medical and Biological Engineering).

This presentation showcases an advanced, modular AI system designed to revolutionize Natural Language Processing (NLP) in healthcare. By integrating Operational Intelligence (OI) with Computer Used Agents (CUAs), the system autonomously extracts, processes, and harmonizes data from Electronic Medical Records (EMRs), IoMT devices, and diagnostic platforms—regardless of format or complexity. A distributed NLP architecture enhances analytical depth by breaking down medical texts into specialized modules, overcoming traditional constraints like limited context windows and memory bottlenecks. Additionally, an optimized Retrieval-Augmented Generation (RAG) component ensures that only the most relevant context is used for reasoning, improving accuracy while reducing computational load.
Two key use cases highlight the system’s impact:

1. Public Health Monitoring: A regional health authority leverages the system to detect emerging health trends, anticipate resource shortages, and respond to disease outbreaks in real time. By integrating and analyzing data from multiple healthcare sources, the system enables proactive decision-making, improving population health management.
2. Personalized Elderly Care: Elderly individuals living independently benefit from continuous, AI-powered remote monitoring. The system detects subtle changes in their health status—such as variations in speech patterns, medication adherence, or biometric trends—and triggers early interventions. This significantly reduces emergency hospital visits and enhances quality of life.

Francesco Emmolo has built his career on a strong passion for technological exploration. He graduated in Electronic Engineering from the University of Florence, having prepared and defended his thesis at the Institute of Electronic Systems at Aalborg University in Denmark, where he also earned a Master's degree.
His professional journey began in the telecommunications sector, where he worked for leading global mobile companies, initially in technical development roles and later transitioning to commercial management positions. He has acquired significant international experience, successfully engaging with multinational environments and securing strategic commercial partnerships with major industrial groups.
In 2008, he founded Sisomo, a startup focused on delivering innovative digital media projects for renowned multinational corporations.
In 2011, he played a key role in launching Taggalo, a pioneering startup in the field of computer vision that won the first ICT prize from Working Capital.
In recent years, within Sisomo, Francesco has increasingly specialized in creating and developing highly innovative ICT projects, with particular emphasis on artificial intelligence solutions.

The integration of technological systems in endoscopy units represents a fundamental step forward in modern healthcare facilities, with significant benefits for patient safety, procedure quality and operational efficiency. This study presents the results of an innovative technological integration project implemented at the endoscopy unit of the Isola Tiberina-Gemelli Hospital in Rome.
This initiative was designed to address several key objectives: standardizing clinical workflows, implementing complete instrument traceability, enhancing documentation capabilities, and optimizing resource utilization. The project's scope extended beyond mere technological implementation, encompassing a complete reorganization of workflows and processes to maximize the benefits of the integrated systems: starting from an initial situation characterized by a database completely disconnected from patient registry data, the complexity of patient traceability was addressed through the integration and interoperability of multiple applications (DIGISTAT, Clean Track, Steelco, Helion).
This harmonized information flow has resulted in a radically innovative system configuration. Through identification bracelets with bar code, operator accountability traceability of the instruments and therefore of the reprocessing phases, each phase of the endoscopic procedure is documented and reported in the final report.
A quantitative and qualitative analysis assessed the impact on workflow efficiency, safety parameters and staff satisfaction. The results demonstrated significant improvements in procedure response times, documentation accuracy and instrument traceability, while maintaining high safety standards.
The success of the project was achieved thanks to the organizational capacity to effectively integrate available resources. The synergy between a qualified team and the implementation of cutting-edge solutions has made it possible to achieve pre-established objectives, guaranteeing efficiency and continuous innovation. The findings from this implementation experience can provide valuable insights for other healthcare facilities considering similar technological integration projects in their endoscopy units.

Clinical Engineer with a Master's Degree, he completed his thesis and worked in AUSL Modena as a manager since 2003, reaching the role of Head of the Simple Operating Unit "Hospitals - Critical Areas" of the Provincial Unified Health Facility (Hospital and AUSL) in 2019.
For 2 years (2018-19) he also covered the role of Adjunt Professor at the Biomedical Engineering Faculty of Bologna, Medical Informatics and Telemedicine Networks course.
In 2020 he moved to the Policlinico Gemelli under the TECHNICAL MANAGEMENT, ICT AND INNOVATION HEALTH TECHNOLOGIES with the role of Director of the Simple Operating Unit Integrated Projects and Technological Innovation, focused on re-engineering of the Laboratory area workflow, including the management of IVD consumables.
From September 2022 to March 2025 he also held the role of Head of the Clinical Engineering Service of the Isola Tiberina Hospital, recently taken over by Gemelli, with the aim of technologically supporting the relaunch of the facility, now complete.

Luca Toschi is the Founder and President of the “scientia Atque usus” Research Center for Generative Communication and the Director of the Generative Communication Lab at the PIN Foundation – Prato Campus of the University of Florence. He is a former Full Professor of Sociology of Cultural and Communicative Processes at the University of Florence. He also founded the Master’s program in Communication for Medical-Scientific and Health Services and currently serves as a member of its steering committee at the University of Florence.
For years, he has been providing consultancy services to national, international and multinational organizations and institutions.
In his book La comunicazione generativa (Apogeo, 2011), he formalized a new vision and mission for communication that underpins the daily methods employed at the two research centers he directs.
He conceived and promoted the development of “Atque,” a Design and Communication System that supports stakeholders, researchers, experts and citizens in developing Generative Communication projects.