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About

Francis Minhthang Bui received the B.A. degree in French language and the B.Sc. degree in electrical engineering from the University of Calgary, Canada, in 2001, and the M.A.Sc. and Ph.D. degrees in electrical engineering from the University of Toronto, Canada, in 2003 and 2009, respectively. He is currently an Associate Professor of Electrical and Computer Engineering with the University of Saskatchewan, Canada. His research interests include information processing and machine learning, with applications in communications and biomedical engineering.

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Skills

Experience

Assistant Professor

University of Saskatchewan

Dec-2020 to Present

Publication

  • dott image December, 2024

DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model

Quorum Sensing Peptides (QSP) are small molecules crucial for microbial communication, enabling bacterial populations to coordinate behaviors such as biofilm formation and virulence. The ide...

  • dott image December, 2024

DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model

Quorum Sensing Peptides (QSP) are small molecules crucial for microbial communication, enabling bacterial populations to coordinate behaviors such as biofilm formation and virulence. The ide...

  • dott image October, 2024

A robust deep learning approach for identification of RNA 5-methyluridine sites

RNA 5-methyluridine (m5U) sites play a significant role in understanding RNA modifications, which influence numerous biological processes such as gene expression and cellular functioning. Co...

  • dott image September, 2024

MLAFP-XN: Leveraging neural network model for development of antifungal peptide identification tool

Infectious fungi have been an increasing global concern in the present era. A promising approach to tackle this pressing concern involves utilizing Antifungal peptides (AFP) to develop an an...

An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection

Diabetic retinopathy (DR) involves retina damage due to diabetes, often leading to blindness. It is diagnosed via color fundus injections, but the manual analysis is cumbersome and error-pro...

  • dott image November, 2023

Development and performance analysis of machine learning methods for predicting depression among menopausal women

Menopause is an obligatory phenomenon in a woman’s life. Some women face mental and physical issues during their menopausal period. Depression is one of the issues some women struggle with...

  • dott image November, 2023

A machine learning approach for risk factors analysis and survival prediction of Heart Failure patients

In this study, we propose machine learning (ML) for risk factors analysis and survival prediction of Heart Failure (HF) patients using a survival dataset. Five supervised ML methods are appl...

  • dott image October, 2023

An Intelligent Thyroid Diagnosis System Utilizing Multiple Ensemble and Explainable Algorithms With Medical Supported Attributes

The widespread impact of thyroid disease and its diagnosis is a challenging task for healthcare experts. The conventional technique for predicting such a vital disease is complex and time-...

  • dott image September, 2023

StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI images

Journal : Journal of King Saud University - Computer and Information Sciences

Predicting fetal brain abnormalities (FBAs) is an urgent global problem, as nearly three of every thousand women are pregnant with neurological abnormalities. Therefore, early detection of F...

  • dott image September, 2023

StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI images

Journal : Journal of King Saud University - Computer and Information Sciences

Predicting fetal brain abnormalities (FBAs) is an urgent global problem, as nearly three of every thousand women are pregnant with neurological abnormalities. Therefore, early detection of F...