Le Nguyen Quoc Khanh

Le Nguyen Quoc Khanh

Associate Professor, Taipei Medical University, In-Service Master Program in Artificial Intelligence in Medicine

Selected publications

Full publication list at (Google Scholar Profile)

Deep Learning-based Integrated System for Intraoperative Blood Loss Quantification in Surgical Sponges

Published in IEEE Journal of Biomedical and Health Informatics, 2024

Recommended citation: Nguyen D., Le M.H.N., Huynh P.K., Le T.Q., Charles-Okezie C., Diaz M.J., Sabet C., Dang H.T., Nguyen T., Nguyen H., Tran M., Le N.Q.K., & Muncey A. (2024). Deep Learning-based Integrated System for Intraoperative Blood Loss Quantification in Surgical Sponges. IEEE Journal of Biomedical and Health Informatics. https://doi.org/10.1109/JBHI.2024.3499852

Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation

Published in Journal of Assisted Reproduction and Genetics, 2024

Recommended citation: Luong T.M.T., Ho N.T., Hwu Y.M., Lin S.Y., Ho J.Y.P., Wang R.S., Lee Y.X., Tan S.J., Lee Y.R., Huang Y.L., Le N.Q.K., & Tzeng C.R. (2024). Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation. Journal of Assisted Reproduction and Genetics, 41, 2349–2358. https://doi.org/10.1007/s10815-024-03178-7

Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data

Published in Journal of Imaging Informatics in Medicine, 2024

Recommended citation: Dang L.H., Hung S.H., Le N.T.N., Chuang W.K., Wu J.Y., Huang T.C., & Le N.Q.K. (2024). Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data. Journal of Imaging Informatics in Medicine. https://doi.org/10.1007/s10278-024-01109-7

Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing

Published in Computers in Biology and Medicine, 2024

Recommended citation: Tran T.O., & Le N.Q.K. (2024). Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing. Computers in Biology and Medicine, 174, 108408. https://doi.org/10.1016/j.compbiomed.2024.108408

Multi-Class Deep Learning Model for Detecting Pediatric Distal Forearm Fractures Based on the AO/OTA Classification

Published in Journal of Imaging Informatics in Medicine, 2024

Recommended citation: Binh L.N., Nhu N.T., Vy V.P.T., Son D.L.H., Hung T.N.K., Bach N., Huy H.Q., Tuan L.V., Le N.Q.K., & Kang J.H. (2024). Multi-Class Deep Learning Model for Detecting Pediatric Distal Forearm Fractures Based on the AO/OTA Classification. Journal of Imaging Informatics in Medicine, 37, 725–733. https://doi.org/10.1007/s10278-024-00968-4

Diffusion-tensor imaging and dynamic susceptibility contrast MRIs improve radiomics-based machine learning model of MGMT promoter methylation status in glioblastomas

Published in Biomedical Signal Processing and Control, 2023

Recommended citation: Minh T.N.T., Le V.H., & Le N.Q.K.. (2023). Diffusion-tensor imaging and dynamic susceptibility contrast MRIs improve radiomics-based machine learning model of MGMT promoter methylation status in glioblastomas. Biomedical Signal Processing and Control, 86, Part A, 105122. https://doi.org/10.1016/j.bspc.2023.105122

MaskDNA-PGD: an innovative deep learning model for detecting DNA methylation by integrating mask sequences and adversarial PGD training as a data augmentation method

Published in Chemometrics and Intelligent Laboratory Systems, 2022

Recommended citation: Zheng Z., Le N.Q.K., & Chua M.C.H. (2023). MaskDNA-PGD: an innovative deep learning model for detecting DNA methylation by integrating mask sequences and adversarial PGD training as a data augmentation method. Chemometrics and Intelligent Laboratory Systems, 14(22), 5562. https://doi.org/10.1016/j.chemolab.2022.104715

Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach

Published in Scientific Reports, 2022

Recommended citation: Do D.T., Yang M.R., Lam L.H.T., Le N.Q.K., & Wu Y.W. (2022). Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach. Scientific Reports, 12, 13412. https://doi.org/10.1038/s41598-022-17707-w

Prospective role and immunotherapeutic targets of sideroflexin protein family in lung adenocarcinoma: evidence from bioinformatics validation

Published in Functional & Integrative Genomics, 2022

Recommended citation: Dang H.H., Ta H.D.K., Nguyen T.T.T., Anuraga G., Wang C.Y., Lee K.H., & Le N.Q.K. (2022). Prospective role and immunotherapeutic targets of sideroflexin protein family in lung adenocarcinoma: evidence from bioinformatics validation. Functional & Integrative Genomics, 22, 1057–1072. https://doi.org/10.1007/s10142-022-00883-3

4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller

Published in International Journal of Fuzzy Systems, 2022

Recommended citation: Huynh T.T., Lin C.M., Nguyen N.P., Le N.Q.K., Vu M.T., Pham D.H., Vu V.P., & Chao F. (2022). 4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller. International Journal of Fuzzy Systems, 24, 2946–2968. https://doi.org/10.1007/s40815-022-01312-0

mCNN-ETC: Identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences

Published in Briefings in Bioinformatics, 2021

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Recommended citation: Ho Q.T., Le N.Q.K., & Ou Y.Y. (2021). mCNN-ETC: Identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences. Briefings in Bioinformatics, 23(1), bbab352. https://doi.org/10.1093/bib/bbab352

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer

Published in International Journal of Molecular Sciences, 2021

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Recommended citation: Le N.Q.K., Kha Q.H., Nguyen V.H., Chen Y.C,, Cheng S.J., Chen C.Y. (2021). Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer. International Journal of Molecular Sciences, 22(17), 9254. https://doi.org/10.3390/ijms22179254

An extensive examination of discovering 5-Methylcytosine Sites in Genome-Wide DNA Promoters using machine learning based approaches

Published in IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021

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Recommended citation: Nguyen T.T.D., Tran T.A., Le N.Q.K., Pham D.M., & Ou Y.Y. (2022). An extensive examination of discovering 5-Methylcytosine Sites in Genome-Wide DNA Promoters using machine learning based approaches. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(1), 87-94. https://doi.org/10.1109/TCBB.2021.3082184

Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI

Published in Computers in Biology and Medicine, 2021

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Recommended citation: Le N.Q.K., Truong N.K.H., Do D.T., Luu H.T.L., Luong H.D., & Huynh T.T. (2021). Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI. Computers in Biology and Medicine, 132, 104320. https://doi.org/10.1016/j.compbiomed.2021.104320

Self-Organizing Double Function-Link Fuzzy Brain Emotional Control System Design for Uncertain Nonlinear Systems

Published in IEEE Transactions on Systems, Man and Cybernetics: Systems, 2020

Recommended citation: Huynh T.T., Lin C.M., Le T.L., Le N.Q.K., Vu V.P., & Chao F. (2022). Self-Organizing Double Function-Link Fuzzy Brain Emotional Control System Design for Uncertain Nonlinear Systems. IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(3), 1852-1868. https://doi.org/10.1109/TSMC.2020.3036404

Incorporating convolutional neural networks and sequence graph transform for identifying multilabel protein Lysine PTM sites

Published in Chemometrics and Intelligent Laboratory Systems, 2020

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Recommended citation: Sua J.N., Lim S.Y., Yulius M.H., Su X., Yapp E.K.Y., Le N.Q.K., Yeh H.Y., & Chua M.C.H. (2020). Incorporating convolutional neural networks and sequence graph transform for identifying multilabel protein Lysine PTM sites. Chemometrics and Intelligent Laboratory Systems, 206, 104171. https://doi.org/10.1016/j.chemolab.2020.104171

Use Chou’s 5-steps rule with different word embedding types to boost performance of electron transport protein prediction model

Published in IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020

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Recommended citation: Nguyen T.T.D., Ho Q.T., Le N.Q.K., Phan D.V., & Ou Y.Y. (2022). Use Chou’s 5-steps rule with different word embedding types to boost performance of electron transport protein prediction model. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(2), 1235-1244. https://doi.org/10.1109/TCBB.2020.3010975

A New Self-Organizing Fuzzy Cerebellar Model Articulation Controller for Uncertain Nonlinear Systems Using Overlapped Gaussian Membership Functions

Published in IEEE Transactions on Industrial Electronics, 2019

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Recommended citation: Huynh T.T., Lin C.M., Le T.L., Cho H.Y., Pham T.T., Le N.Q.K., Chao F. (2020). A New Self-Organizing Fuzzy Cerebellar Model Articulation Controller for Uncertain Nonlinear Systems Using Overlapped Gaussian Membership Functions. IEEE Transactions on Industrial Electronics, vol. 67, no. 11, pp. 9671-9682. https://doi.org/10.1109/TIE.2019.2952790

Classifying Promoters by Interpreting the Hidden Information of DNA Sequences via Deep Learning and Combination of Continuous FastText N-Grams

Published in Frontiers in Bioengineering and Biotechnology, 2019

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Recommended citation: Le N.Q.K., Yapp E.K.Y., Nagasundaram N., & Yeh H.Y. (2019). Classifying Promoters by Interpreting the Hidden Information of DNA Sequences via Deep Learning and Combination of Continuous FastText N-Grams. Frontiers in Bioengineering and Biotechnology, 7:305. https://doi.org/10.3389/fbioe.2019.00305

Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture

Published in Computational and Structural Biotechnology Journal, 2019

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Recommended citation: Le N.Q.K., Yapp E.K.Y., Nagasundaram N., Chua M.C.H., & Yeh H.Y. (2019). Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture. Computational and Structural Biotechnology Journal, 17, 1245-1254. https://doi.org/10.1016/j.csbj.2019.09.005

A sequence-based approach for identifying recombination spots in Saccharomyces cerevisiae by using hyper-parameter optimization in FastText and support vector machine

Published in Chemometrics and Intelligent Laboratory Systems, 2019

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Recommended citation: Do D.T., & Le N.Q.K. (2019). A sequence-based approach for identifying recombination spots in Saccharomyces cerevisiae by using hyper-parameter optimization in FastText and support vector machine. Chemometrics and Intelligent Laboratory Systems, 194, 103855. https://doi.org/10.1016/j.chemolab.2019.103855

Fertility-GRU: Identifying Fertility-Related Proteins by Incorporating Deep-Gated Recurrent Units and Original Position-Specific Scoring Matrix Profiles

Published in Journal of Proteome Research, 2019

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Recommended citation: Le, N.Q.K. (2019). Fertility-GRU: Identifying Fertility-Related Proteins by Incorporating Deep-Gated Recurrent Units and Original Position-Specific Scoring Matrix Profiles. Journal of Proteome Research, 18(9), 3503-3511. https://doi.org/10.1021/acs.jproteome.9b00411

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins

Published in Journal of Computational Chemistry, 2017

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Recommended citation: Le N.Q.K., Ho Q.T., & Ou Y.Y. (2017). Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins. Journal of Computational Chemistry, 38(23), 2000-2006. https://doi.org/10.1002/jcc.24842