Proximity-based solutions for optimizing autism spectrum disorder treatment

Integrating clinical and process data for personalized care

Bibliographic Data

ID15520893
AuthorsAnnarita Vignapiano (ASL Roma), Francesco Monaco (0000-0002-5617-7943, ASL Roma), Stefania Landi (0000-0002-3822-4451, ASL Roma, corresponding author), Luca Steardo (0000-0002-7077-3506, Magna Graecia University), Carlo Mancuso, Claudio Pagano (0000-0002-4335-8411), Gianvito Petrillo, Alessandra Marenna (0000-0003-0960-2924, European Biomedical Research Institute of Salerno), Martina Piacente (0000-0002-1303-4117, European Biomedical Research Institute of Salerno), Stefano Leo (European Biomedical Research Institute of Salerno), Carminia Marina Ingenito (0000-0001-8849-0355, European Biomedical Research Institute of Salerno), Rossella Bonifacio, Benedetta Di Gruttola (ASL Roma), Marco Solmi (0000-0003-4877-7233, University of Ottawa), Maria Pontillo (0000-0002-0083-0093, Bambino Gesù Children's Hospital), Giorgio Di Lorenzo (0000-0002-0576-4064, University of Rome Tor Vergata), Alessio Fasano (0000-0002-2134-0261, Harvard University), Giulio Corrivetti (ASL Roma)
Year2025
Volume15
Pages1512818-1512818
Publication date2025-01-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2024.1512818
PMID39911557
OpenAlexW4406703308
LanguageEN
References cited35

Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, presenting challenges in social communication, repetitive behaviors, and sensory processing. Despite its prevalence, diagnosis can be lengthy, and access to appropriate treatment varies greatly. This project utilizes the power of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve Autism Spectrum Disorder diagnosis and treatment. A central data hub, the Master Data Plan (MDP), will aggregate and analyze information from diverse sources, feeding AI algorithms that can identify risk factors for ASD, personalize treatment plans based on individual needs, and even predict potential relapses. Furthermore, the project incorporates a patient-facing chatbot to provide information and support. By integrating patient data, empowering individuals with ASD, and supporting healthcare professionals, this platform aims to transform care accessibility, personalize treatment approaches, and optimize the entire care journey. Rigorous data governance measures will ensure ethical and secure data management. This project will improve access to care, personalize treatments for better outcomes, shorten wait times, boost patient involvement, and raise ASD awareness, leading to better resource allocation. This project marks a transformative shift toward data-driven, patient-centred ASD care in Italy. This platform enhances treatment outcomes for individuals with ASD and provides a scalable model for integrating AI into mental health, establishing a new benchmark for personalized patient care. Through AI integration and collaborative efforts, it aims to redefine mental healthcare standards, enhancing the well-being for individuals with ASD

Autism · Autism spectrum disorder · Health care · Psychiatry · Autism Spectrum Disorder Research · Computer Science · Medicine · Psychology · Artificial Intelligence

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