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Clinical Trial

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

NCT: NCT07652931 · NOT_YET_RECRUITING

NCT IDNCT07652931
StatusNOT_YET_RECRUITING
Start Date2026-08-01
Completion2029-08-01
SponsorIRCCS San Raffaele (OTHER)
First posted
Last updated

Brief Summary

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.

Frequently Asked Questions

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

Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns is a clinical trial registered under NCT07652931. Current status: NOT_YET_RECRUITING.

What is the status of NCT07652931?

The current status of NCT07652931 (Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns) is: NOT_YET_RECRUITING.

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

Using Artificial Intelligence to Detect Early Signs of Alzheimer's Disease in People With Memory Concerns started on 2026-08-01.

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Official Source

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Data sourced from ClinicalTrials.gov API. For the most current status, refer to the official record.