Nguyen-Quoc-Khanh Le
Orcid: 0000-0003-4896-7926
According to our database1,
Nguyen-Quoc-Khanh Le
authored at least 56 papers
between 2016 and 2026.
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Bibliography
2026
A unified graph-based approach for protein function prediction using AlphaFold structures and sequence features.
Comput. Biol. Chem., 2026
2025
MLG2Net: Molecular Global Graph Network for Drug Response Prediction in Lung Cancer Cell Lines.
J. Medical Syst., December, 2025
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.
J. Medical Syst., December, 2025
Deep Learning-Based Integrated System for Intraoperative Blood Loss Quantification in Surgical Sponges.
IEEE J. Biomed. Health Informatics, September, 2025
Graph-Theoretic Consistency for Robust and Topology-Aware Semi-Supervised Histopathology Segmentation.
CoRR, September, 2025
AI-driven multi-modal framework for prognostic modeling in glioblastoma: Enhancing clinical decision support.
Comput. Medical Imaging Graph., 2025
Integrating CNN and Bi-LSTM for protein succinylation sites prediction based on Natural Language Processing technique.
Comput. Biol. Medicine, 2025
DeepGPT-DILI: Integrating Graph Convolutional Networks and Large Language Model Embeddings for Accurate Drug-Induced Liver Injury Prediction.
Proceedings of the Emerging LLM/LMM Applications in Medical Imaging, 2025
2024
VF-Pred: Predicting virulence factor using sequence alignment percentage and ensemble learning models.
Comput. Biol. Medicine, January, 2024
Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data.
J. Imaging Inform. Medicine, 2024
Multi-Class Deep Learning Model for Detecting Pediatric Distal Forearm Fractures Based on the AO/OTA Classification.
J. Imaging Inform. Medicine, 2024
Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.
Comput. Biol. Medicine, 2024
Using a hybrid neural network architecture for DNA sequence representation: A study on N4-methylcytosine sites.
Comput. Biol. Medicine, 2024
RNA-ModX: a multilabel prediction and interpretation framework for RNA modifications.
Briefings Bioinform., 2024
RF-Lung-DR: Integrating Biological and Drug SMILES Features in a Random Forest-Based Drug Response Predictor for Lung Cancer Cell Lines.
Proceedings of the Trustworthy Artificial Intelligence for Healthcare, 2024
SISU: A Holistic Self-training Framework on Semi-supervised White Blood Cell Segmentation.
Proceedings of the Trustworthy Artificial Intelligence for Healthcare, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
Enhancing Protein Sequence Classification with a Fuzzy Neural Network: A Study in Anticancer Peptide Identification.
Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2024
2023
A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas.
Medical Biol. Eng. Comput., October, 2023
Diffusion-tensor imaging and dynamic susceptibility contrast MRIs improve radiomics-based machine learning model of MGMT promoter methylation status in glioblastomas.
Biomed. Signal Process. Control., September, 2023
Sequence-based prediction model of protein crystallization propensity using machine learning and two-level feature selection.
Briefings Bioinform., September, 2023
Development and Validation of CT-Based Radiomics Signature for Overall Survival Prediction in Multi-organ Cancer.
J. Digit. Imaging, June, 2023
Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding.
Briefings Bioinform., January, 2023
Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug-Food Interactions from Chemical Structures.
Sensors, 2023
An MRI-based radiomics signatures for overall survival prediction of gliomas patients.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Predicting Tumor Mutational Burden and Survival in Head and Neck Squamous Cancer Patients Using Machine Learning and Bioinformatics Approaches.
Proceedings of the 14th ACM International Conference on Bioinformatics, 2023
A Sequence-Based Prediction Model of Vesicular Transport Proteins Using Ensemble Deep Learning.
Proceedings of the 14th ACM International Conference on Bioinformatics, 2023
2022
Self-Organizing Double Function-Link Fuzzy Brain Emotional Control System Design for Uncertain Nonlinear Systems.
IEEE Trans. Syst. Man Cybern. Syst., 2022
An Extensive Examination of Discovering 5-Methylcytosine Sites in Genome-Wide DNA Promoters Using Machine Learning Based Approaches.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Use Chou's 5-Steps Rule With Different Word Embedding Types to Boost Performance of Electron Transport Protein Prediction Model.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022
Identifying SNARE Proteins Using an Alignment-Free Method Based on Multiscan Convolutional Neural Network and PSSM Profiles.
J. Chem. Inf. Model., 2022
4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller.
Int. J. Fuzzy Syst., 2022
BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection.
Comput. Biol. Chem., 2022
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 Bioinform., 2022
Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems.
Appl. Intell., 2022
Prediction of Protein-Protein Interactions through Deep Learning Based on Sequence Feature Extraction and Interaction Network.
Proceedings of the IEEE Biomedical Circuits and Systems Conference, 2022
2021
Prediction of FMN Binding Sites in Electron Transport Chains Based on 2-D CNN and PSSM Profiles.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels.
Comput. Biol. Medicine, 2021
Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI.
Comput. Biol. Medicine, 2021
FAD-BERT: Improved prediction of FAD binding sites using pre-training of deep bidirectional transformers.
Comput. Biol. Medicine, 2021
A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information.
Briefings Bioinform., 2021
Using deep neural networks and biological subwords to detect protein S-sulfenylation sites.
Briefings Bioinform., 2021
2020
A New Self-Organizing Fuzzy Cerebellar Model Articulation Controller for Uncertain Nonlinear Systems Using Overlapped Gaussian Membership Functions.
IEEE Trans. Ind. Electron., 2020
DeepETC: A deep convolutional neural network architecture for investigating and classifying electron transport chain's complexes.
Neurocomputing, 2020
2019
SNARE-CNN: a 2D convolutional neural network architecture to identify SNARE proteins from high-throughput sequencing data.
PeerJ Comput. Sci., 2019
Using two-dimensional convolutional neural networks for identifying GTP binding sites in Rab proteins.
J. Bioinform. Comput. Biol., 2019
Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles.
Comput. Methods Programs Biomed., 2019
ET-GRU: using multi-layer gated recurrent units to identify electron transport proteins.
BMC Bioinform., 2019
2018
Incorporating post translational modification information for enhancing the predictive performance of membrane transport proteins.
Comput. Biol. Chem., 2018
DeepEfflux: a 2D convolutional neural network model for identifying families of efflux proteins in transporters.
Bioinform., 2018
2017
Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.
J. Comput. Chem., 2017
2016
Incorporating efficient radial basis function networks and significant amino acid pairs for predicting GTP binding sites in transport proteins.
BMC Bioinform., 2016
Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.
BMC Bioinform., 2016
Using Deep Learning with Position Specific Scoring Matrices to Identify Efflux Proteins in Membrane and Transport Proteins.
Proceedings of the 16th IEEE International Conference on Bioinformatics and Bioengineering, 2016