Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns

AHEAD is a prospective, longitudinal, risk-stratified single-arm interventional study enrolling 300 patients with Subjective Cognitive Decline (SCD) at IRCCS San Raffaele Hospital, Milan, Italy. The study uses artificial intelligence (AI) to integrate multimodal data - including MRI, EEG, Optical Coherence Tomography (OCT), neuropsychological assessments, and plasma biomarkers - to identify individuals with underlying Alzheimer's disease (AD) biology and predict cognitive progression. Only participants found to be AD plasma biomarker positive (SCD+) undergo longitudinal follow-up at 12 and 24 months. Participants classified as high risk additionally receive a 6-month personalized multidisciplinary intervention combining high-frequency transcranial magnetic stimulation (TMS), digital cognitive training, structured physical exercise, and targeted management of modifiable vascular and behavioral risk factors.

Inclusion Criteria: 1. Diagnosis of Subjective Cognitive Decline (SCD) according to international diagnostic criteria (Jessen et al., 2014). 2. Self-experienced persistent decline in cognitive capacity in comparison with a previously normal status and unrelated to an acute event. 3. Normal age-, gender-, and education-adjusted performance on standardized cognitive tests used to classify mild cognitive impairment (MCI) or prodromal AD. 4. Age greater than or equal to 40 years. 5. Native Italian Speaker. 6. Stable pharmacological treatment for at least 4 weeks prior to enrollment. 7. Provision of oral and written informed consent to study participation. Exclusion Criteria: 1. Presence of MCI, prodromal AD, or dementia. 2. Any major systemic, psychiatric, or neurological disturbance. 3. Medical conditions or substance abuse that could interfere with cognition. 4. Pacemaker and/or other implanted neurostimulation devices in the head/neck district. 5. Contraindications to undergoing MRI examination. 6. Brain damage at routine MRI, including extensive cerebrovascular disorders. 7. Traumatic or surgical wounds that could determine a risk of infection at the site of non-invasive stimulation. 8. Scalp alterations that could determine the spread of excessive current from the device. 9. Known history of epilepsy (due to small risk of seizure induction from rTMS in epileptic patients). 10. Denial of oral and written informed consent to study participation.