Publications

Machine Learning-based ALS Diagnosis Using Gene Expression Data

Published in RIVF International Conference on Computing and Communication Technologies (RIVF), 2023

We explore the gene expression of the Amyotrophic lateral sclerosis (ALS) - an rare disease that lacks of research nowadays, especially in Vietnam. An sequential of gene selection and gene ranking are considered as the effective procedure for identify signature biomarker realted to ALS. Besides, an powerful diagnosis model is constructed based on the selecte genes which perform overpower the current study of prediction ALS disease.(Under review)

Recommended citation: Please cite this paper via IEEE citation format https://longvd336.github.io/files/2023281368.pdf

Efficient Machine Learning-based Gene Selection Exploiting Immune-related Biomarkers and Recursive Feature Elimination for Sepsis Diagnosis

Published in International Symposium on Information and Communication Technology (SOICT 2023), 2023

We develop a novel approach leverage the effectiveness of Principal Component Analysis and Machine Learning to select potential gene biomarker.

Recommended citation: Please cite this paper via IEEE citation format https://longvd336.github.io/files/soict2023-6182.pdf