26 Result(s)
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Nguyen Quoc Khanh Le
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Article
Hematoma expansion prediction: still navigating the intersection of deep learning and radiomics
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Article
MASPP and MWASP: multi-head self-attention based modules for UNet network in melon spot segmentation
Sweet melon, and in particular, spotted melon, is one of the most profitable fruit crops for farmers in the international market. As the spot ratio impacts the melon’s visual appeal, it plays a significant rol...
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Article
Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data
Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed to develop a prediction model for NPC survival by har...
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Article
Multi-Class Deep Learning Model for Detecting Pediatric Distal Forearm Fractures Based on the AO/OTA Classification
Common pediatric distal forearm fractures necessitate precise detection. To support prompt treatment planning by clinicians, our study aimed to create a multi-class convolutional neural network (CNN) model for...
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Article
Artificial intelligence in time-lapse system: advances, applications, and future perspectives in reproductive medicine
With the rising demand for in vitro fertilization (IVF) cycles, there is a growing need for innovative techniques to optimize procedure outcomes. One such technique is time-lapse system (TLS) for embryo incuba...
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Article
Predicting emerging drug interactions using GNNs
EmerGNN is a flow-based graph neural network (GNN) approach that advances on conventional methodologies for predicting drug–drug interactions in emerging drugs by effectively leveraging biomedical networks.
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Article
Non-destructive classification of melon sweetness levels using segmented rind properties based on semantic segmentation models
Melon is one of the most consumed crops worldwide and has high marketability. Consumers prefer sweet melons. However, the nondestructive determination of melon sweetness is challenging because of its thick rin...
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Article
A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas
Lower-grade gliomas (LGG) can eventually progress to glioblastoma (GBM) and death. In the context of the transfer learning approach, we aimed to train and test an MRI-based radiomics model for predicting survi...
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Article
Hyper-methylation of ABCG1 as an epigenetics biomarker in non-small cell lung cancer
Non-small cell lung cancer (NSCLC) is the most prevalent histological type of lung cancer and the leading cause of death globally. Patients with NSCLC have a poor prognosis for various factors, and a late diag...
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Article
Development and Validation of CT-Based Radiomics Signature for Overall Survival Prediction in Multi-organ Cancer
The malignant tumors in nature share some common morphological characteristics. Radiomics is not only images but also data; we think that a probability exists in a set of radiomics signatures extracted from CT...
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Chapter and Conference Paper
Enhanced Prediction of mRNA Subcellular Localization Using a Novel Ensemble Learning and Hybrid Approach
Unraveling the subcellular localization of mRNA is an imperative aspect in the realm of biotechnology. This resolution can illuminate the inner workings of genetic regulatory mechanisms, gene expression modali...
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Chapter and Conference Paper
Incorporating Natural Language-Based and Sequence-Based Features to Predict Protein Sumoylation Sites
The incidence of thyroid cancer and breast cancer is increasing every year, and the specific pathogenesis is unclear. Post-translational modifications are an important regulatory mechanism that affects the fun...
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Article
Prospective role and immunotherapeutic targets of sideroflexin protein family in lung adenocarcinoma: evidence from bioinformatics validation
As lung cancer remains the leading cause of cancer deaths globally, characterizing the tumor molecular profiles is crucial to tailoring treatments for individuals at advanced stages. Cancer cells exhibit stron...
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Article
4-D Memristive Chaotic Systems-Based Audio Secure Communication Using Dual-Function-Link Fuzzy Brain Emotional Controller
This paper aims to propose an efficient algorithm for the synchronization of 4-D memristive chaotic systems and their applications for audio secure communication. A dual-function-link (DFL) fuzzy brain emotion...
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Article
Open AccessImproving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach
O6-Methylguanine-DNA-methyltransferase (MGMT) promoter methylation was shown in many studies to be an important predictive biomarker for temozolomide (TMZ) resistance and poor progression-free survival in glio...
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Article
Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems
This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multil...
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Article
Using k-mer embeddings learned from a Skip-gram based neural network for building a cross-species DNA N6-methyladenine site prediction model
This study used k-mer embeddings as effective feature to identify DNA N6-Methyladenine sites in plant genomes and obtained improved performance without substantial effort in feature extraction, combination and...
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Article
Open AccessTNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Cytokines are a class of small proteins that act as chemical messengers and play a significant role in essential cellular processes including immunity regulation, hematopoiesis, and inflammation. As one import...
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Article
Open AccessiEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks
Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transcription and translation). Having high locational variation and free scattering in 98% of non-encoding genomes, enhancer i...
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Article
Open AccessClassification of adaptor proteins using recurrent neural networks and PSSM profiles
Adaptor proteins are carrier proteins that play a crucial role in signal transduction. They commonly consist of several modular domains, each having its own binding activity and operating by forming complexes ...
