Supporting patients and clinicians during the breast cancer care path with AI: The Arianna solution

The onset of cancer disease is a traumatic experience for both patients and their families that suddenly change the patient's life and is accompanied by important physical, emotional, and psycho-social problems. The complexity of this scenario has been exacerbated by the COVID-19 pandemic which dramatically affected the continuity of the provision of optimal care to chronic patients. Telemedicine can support the management of oncology care paths by furnishing a suite of effective and efficient tools to monitor the therapies of cancer patients. In particular, this is a suitable setting for therapies that are administered at home. In this paper, we present an AI-based system, called Arianna, designed and implemented to support and monitor patients treated by the professionals belonging to the Breast Cancer Unit Network (BCU-Net) along the entire clinical path of breast cancer treatment. We describe in this work the three modules composing the Arianna system (the tools for patients and clinicians, and the symbolic AI-based module). The system has been validated in a qualitative way and we demonstrated how the Arianna solution reached a high level of acceptability by all types of end-users by making it suitable for a concrete integration into the daily practice of the BCU-Net

Accessible and Inclusive Mobile Application for Social Support and m-Health in Forced Isolation: SAFE TALK

The condition of forced isolation due to the Covid-19 Pandemic clearly highlighted the importance of social support. Indeed, the absence of interaction with families and friends in the presence can lead to feelings of loneliness, abandonment, psychological discomfort, anxiety, and depression, especially for the elderly. On this premise, adopting a user-centered approach, an app for social and professional support SAFE TALK was created and evaluated recruiting end users. The participatory activities involving elderly informed the design of the app prototypes, while at a second stage two samples of target users (i.e., elderly and psychologists) were considered in the evaluations of the SAFE TALK app. The performance, usability, accessibility, and user experience of the app were tested. Findings showed that despite a slightly lower performance of the elderly, both groups of individuals positively evaluated the usability, accessibility, and user experience of the app. SAFE TALK was appreciated by the elderly as a potential supportive tool in case of forced isolation to reach their social sphere and eventually a professional. Psychologists reported the relevance of the app as a tool to remotely support people in conditions of need

Organisational models supported by technology for the management of diabetic disease and its complications in a diabetic clinic setting: study protocol for a randomised controlled trial targeting type 2 diabetes individuals with non-ideal glycaemic values (Telemechron study)

Introduction: Type 2 diabetes mellitus (T2DM) is a non-communicable disease representing one of the most serious public health challenges of the twenty-first century. Its incidence continues to rise in both developed and developing countries, causing the death of 1.5 million people every year. The use of technology (e.g. smartphone application-App) in the health field has progressively increased as it has been proved to be effective in helping individuals manage their long-term diseases. Therefore, it has the potential to reduce the use of health service and its related costs. The objective of this study is to evaluate the impact of using a digital platform called "TreC Diabete" embedded into a novel organisational asset targeting poorly controlled T2DM individuals in the Autonomous Province of Trento (PAT), Italy. Methods: This trial was designed as a multi-centre, open-label, randomised, superiority study with two parallel groups and a 1:1 allocation ratio. Individuals regularly attending outpatient diabetes clinics, providing informed consent, are randomised to be prescribed TreC Diabete platform as part of their personalised care plan. Healthcare staff members will remotely assess the data shared by the participants through the App by using a dedicated online medical dashboard. The primary end-point is the evaluation of the Hb1Ac level at 12-month post-randomisation. Data will be analysed on an intention-to-treat (ITT) basis. Discussion: This trial is the first conducted in the PAT area for the use of an App specifically designed for individuals with poorly controlled T2DM. If the effects of introducing this specific App within a new organisational asset are positive, the digital platform will represent a possible way for people diagnosed with T2DM to better manage their health in the future. Results will be disseminated through conferences and peer-reviewed journals once the study is completed. Trial registration: ClinicalTrials.gov NCT05629221. Registered on November 29, 2022, prior start of inclusion