Local post-hoc interpretable machine learning model for prediction of dementia in young adults

Title

Local post-hoc interpretable machine learning model for prediction of dementia in young adults

Creator

Sharma V.; Midhunchakkaravarthy D.

Description

Dementia is still the prevailing brain disease with late diagnosis. There is a large increase in dementia disease among young adults. The major reason is over indulgence of young adults on social media resulting in denial of disease and delayed clinical diagnosis. Dementia is preventable and curable if diagnosed at an early stage, however, no attempts are being made to mitigate dementia in young adults. Today artificial intelligence (AI) based advanced technology with real-life consultations in clinical or remote setups are proved beneficial and is used to detect dementia. Most AI-based test is dependent on computer-aided diagnosis (CAD) tools and uses non-invasive imaging technology such as magnetic resonance imaging (MRI) data for disease diagnosis. In this paper, a local post-hoc interpretable machine learning (LPIML) model for prediction of dementia in young adults is proposed. The performance parameters are computed and compared based on accuracy, specificity, precision, F1 score and recall. The proposed work yields 98.87% training accuracy on original images and 99.31% training accuracy on morphologically enhanced images. The performance results are intrinsic and intuitive in learning the prediction results of individual case. The adoption of the proposed work will accelerate the diagnosis process in the era of digital healthcare. 2023 Institute of Advanced Engineering and Science. All rights reserved.

Source

Indonesian Journal of Electrical Engineering and Computer Science, Vol-32, No. 3, pp. 1569-1579.

Date

2023-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Artificial intelligence; Brain diseases; Classification model first; Convolutional neural network; Image segmentation techniques; U-net structure

Coverage

Sharma V., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia, Computer Science Department, CHRIST (Deemed to be University), Delhi-NCR Campus, India, Department of Computer Science and Multimedia, Lincoln University College Petaling Jaya, Selangor, Malaysia; Midhunchakkaravarthy D., Department of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia

Rights

All Open Access; Gold Open Access

Relation

ISSN: 25024752

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijeecs.v32.i3.pp1569-1579

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178303803&doi=10.11591%2fijeecs.v32.i3.pp1569-1579&partnerID=40&md5=d9bb3d9d67c60cc6ce18a61bd79e416e