Introduction: Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by diverse motor and non-motor symptoms. AI appears to be the elephant in the neurologist's room, albeit offering transformative potential in early diagnosis, personalized care, and treatment optimization, addressing the complexities of PD management. Methods: A PubMed review analyzed AI's role in PD care, focusing on multimodal data, clinician-in-the-loop models, and validation strategies to enhance clinical applicability while addressing ethical concerns. Results: Thirty-nine studies met inclusion criteria. While progress is evident, challenges include limited independent validation, small sample sizes, and inconsistent clinician involvement. Key trends show growing interest in multimodal data and predictive modelling, though gaps in transparency persist. Conclusions: AI holds promise for improving PD management, yet robust validation, interdisciplinary collaboration, and clearer clinician roles are essential for advancing patient-centered care and fostering trust in AI-driven innovations.
The third wheel or the game changer? How AI could team up with neurologists in Parkinson's care
Lorenzo Gios
;Giuseppe Jurman
2025-01-01
Abstract
Introduction: Parkinson's disease (PD) is a progressive neurodegenerative disorder marked by diverse motor and non-motor symptoms. AI appears to be the elephant in the neurologist's room, albeit offering transformative potential in early diagnosis, personalized care, and treatment optimization, addressing the complexities of PD management. Methods: A PubMed review analyzed AI's role in PD care, focusing on multimodal data, clinician-in-the-loop models, and validation strategies to enhance clinical applicability while addressing ethical concerns. Results: Thirty-nine studies met inclusion criteria. While progress is evident, challenges include limited independent validation, small sample sizes, and inconsistent clinician involvement. Key trends show growing interest in multimodal data and predictive modelling, though gaps in transparency persist. Conclusions: AI holds promise for improving PD management, yet robust validation, interdisciplinary collaboration, and clearer clinician roles are essential for advancing patient-centered care and fostering trust in AI-driven innovations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.