An advanced Artificial Intelligence platform for a personalised treatment of Eating Disorders

Abstract

Introduction: Eating Disorders (EDs) affect individuals globally and are associated with significant physical and mental health challenges. However, access to adequate treatment is often hindered by societal stigma, limited awareness, and resource constraints.

Methods: The project aims to utilize the power of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve EDs diagnosis and treatment. The Master Data Plan (MDP) will collect and analyze data from diverse sources, utilize AI algorithms for risk factor identificat io n, treatment planning, and relapse prediction, and provide a patient-facing chatbot for information and support. This platform will integrate patient data, support healthcare professionals, and empower patients, thereby enhancing care accessibility, personalizing treatment plans, and optimizing care pathways. Robust data governance measures will ensure ethical and secure data management.

Results: Anticipated outcomes include enhanced care accessibility and efficiency, personalized treatment plans leading to improved patient outcomes, reduced waiting lists, heightened patient engagement, and increased awareness of EDs with improved resource allocation.

Discussion: This project signifies a pivotal shift towards data-driven, patient-centered ED care in Italy. By integrat ing AI and promoting collaboration, it seeks to redefine mental healthcare standards and foster better well- being among individuals with EDs.

Keywords: artificial intelligence; data-driven approach; early identification; eating disorders; personalized treatment.

Figure 1

The diagram provides a high-level view of the components and how they interact through the different phases of the data life cycle.