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AD/PD 2024 | Using machine learning to predict progression from subject cognitive decline to Alzheimer’s disease

Salvatore Mazzeo, MD, PhD, Vita-Salute San Raffaele University, Milan & AOU Careggi, Florence, Italy, discusses the emerging findings of the PREVIEW study that employed machine learning (ML) to predict progression risk from subjective cognitive decline (SCD) to Alzheimer’s disease (AD). SCD has been evidenced as one of the earliest symptoms of AD, preceding mild cognitive impairment. This study represents one of the first attempts to apply ML to predict AD in a SCD population, with a 14-year follow up. Patients diagnosed with SCD underwent clinical, neurologic, and neuropsychological examination to develop a ML model. ML demonstrated a high predictive accuracy in identifying SCD patient progression outcomes and delineated the most important clinical features that must inform clinical decision making at baseline. As there are no existing clinical protocols to manage SCD, ML represents a promising prognostic avenue to identify patients that require more intervention. This interview took place at the AD/PD™ 2024 congress in Lisbon, Portugal.

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