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Classification of Inflammatory Gene Expression Patterns with Machine Learning Models

conference contribution
posted on 2024-01-30, 02:43 authored by Y Ay, YH Choo, Asim BhattiAsim Bhatti, Chee Peng LimChee Peng Lim
Dementia is a complex neurological disorder characterized by a progressive decline in cognitive functions. Recent studies have suggested a link between neuroinflammation and the development of dementia, particularly in Alzheimer's disease. This study focuses on the analysis of inflammatory gene expression patterns in the parietal cortex (PCx) and temporal cortex (TCx) from a human brain RNA sequence data set, aiming to derive insights into the underlying genetic link associated with dementia, as well as prediction of dementia. Using five machine learning and statistical methods, our study reveals better detection and classification of dementia patients using PCx-related gene patterns, as compared with those from the TCx. Our findings support the hypothesis that the PCx plays a significant role in neuroinflammatory responses associated with dementia. Based on this preliminary study, machine learning models offer a useful approach to recognize inflammatory gene expression patterns and providing a valuable biomarker analysis and prediction for dementia diagnosis.

History

Volume

00

Pagination

115-119

Location

Urumqi, China

Start date

2023-08-04

End date

2023-08-06

ISBN-13

9798350324303

Language

eng

Title of proceedings

2023 IEEE 4th International Conference on Pattern Recognition and Machine Learning, PRML 2023

Event

2023 IEEE 4th International Conference on Pattern Recognition and Machine Learning (PRML)

Publisher

IEEE

Place of publication

Piscataway, N.J.