همایش بین المللی هوش مصنوعی

صفحه اصلی / اولین همایش بین المللی هوش مصنوعی

Aβ42/Aβ40 ratio prediction using MRI images features for Alzheimer’s Early Detection

نویسندگان :

Atefe Aghaei¹ Mohsen Ebrahimi Moghaddam²

1- Computer Science and Engineering Department, Shahid Beheshti University 2- Computer Science and Engineering Department, Shahid Beheshti University

کلمات کلیدی :

3DCNN،Random Forest Regression،Alzheimer’s Disease،MRI،Aβ42/Aβ40 ratio

چکیده :

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and the accumulation of amyloid-beta plaques. Early detection is crucial for timely intervention, and the Aβ42/Aβ40 ratio is a key biomarker for identifying amyloid deposition. In this study, we propose a method to predict the Aβ42/Aβ40 ratio using the extracted features from MRI images using 3D Convolutional Neural Network (3D CNN). Moreover, Random Forest Regression is employed to obtain the relationship between MRI features and the Aβ42/Aβ40 ratio. Our results demonstrate a strong correlation (r = 0.72) between the predicted and actual Aβ42/Aβ40 ratios, effectively predicting amyloid accumulation. This result also makes the proposed feature extraction model more reliable. By leveraging MRI and molecular biomarkers such as the Aβ42/Aβ40 ratio, the proposed method provides valuable insights into disease progression and early diagnosis.