Intelligent diagnosis strategies of Alzheimer's disease

Bo Li; Yixin Cui

doi:10.1117/12.3036865

13 July 2024 Intelligent diagnosis strategies of Alzheimer's disease

Bo Li, Yixin Cui

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132082G (2024) https://doi.org/10.1117/12.3036865
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

Alzheimer's disease (AD) is a neurodegenerative disease with an insidious onset and a brain disorder often found in the middle-aged and elderly population, posing a serious health risk to the middle-aged and elderly. For the large database of AD patients that can be used for patient diagnosis, there is a general concern that its reliance on current medical classifications leads to ambiguous results and hides important scientific information. Therefore, it is important to know how to use mathematical models to assist experts in constructing AD recognition models and accurately diagnosing the disease. This paper propose a search and diagnosis classification strategy that combines supervised and unsupervised learning to obtain data information about patients from ANDI databases using external medical knowledge, which includes structural brain features and cognitive-behavioral features. To reduce the data volume of clinical measures, after preprocessing the data, supervised random forest classification is applied to filter features with feature importance greater than 0.025, and then unsupervised learning including PCR and K-means clustering is used to create new clinical performance categories based on the features selected by the clusters. The results of the defined tri- and quintuple classification are more precise, and this paper's strategy aims to establish a connection between potential biomarkers and clinical functional performance. The screened data is also meaningful, providing a basis for interpretation and comparison for the classification and diagnosis of AD by AD clinical medicine experts and opening up more opportunities for the early detection of AD patients.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bo Li and Yixin Cui "Intelligent diagnosis strategies of Alzheimer's disease", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132082G (13 July 2024); https://doi.org/10.1117/12.3036865

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Alzheimer disease

Diagnostics

Random forests

Data modeling

Brain

Databases

Brain diseases

Show All Keywords

Keywords/Phrases

Search In:

Publication Years