Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment
The incorporation of AI methodologies such as GNNs and MLPs into clinical settings holds promise for enhancing the diagnosis and management of Alzheimer's disease and mild cognitive impairment. By deploying these advanced computational techniques, clinicians could see a reduction in diagnostic errors, facilitating earlier, more precise interventions, and likely to lead to significantly improved outcomes for patients.
Authors
- Giuseppe Alessio Platania (ORCID: https://orcid.org/0000-0003-1927-6288)
- Pierfrancesco Sarti (ORCID: https://orcid.org/0009-0009-4342-8641)
- Johanna Maria Catharina Blom (ORCID: https://orcid.org/0000-0002-4974-1964)
- Veronica Rivi (ORCID: https://orcid.org/0000-0002-8413-4510)
- Mario Santagati
- Claudia Savia Guerrera (ORCID: https://orcid.org/0000-0002-3744-8306)
- Filippo Caraci (ORCID: https://orcid.org/0000-0002-9867-6054)
- Sophie Tascedda
Institutions
- University of Modena and Reggio Emilia (IT)
- University of Zurich (CH)
- Centre Hospitalier Universitaire Vaudois (CH)
- University of Catania (IT)
- Oasi Maria SS (IT)
- Hôpital Orthopédique de la Suisse Romande (CH)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
- University of Lausanne (CH)
Publication Details
- Journal
- Frontiers in Aging Neuroscience
- Published
- 2024-11-29
- DOI
- https://doi.org/10.3389/fnagi.2024.1488050
- Citations
- 11
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 4.24