Binh P. Nguyen

Binh P. Nguyen
Victoria University of Wellington · School of Mathematics and Statistics

Ph.D. (National University of Singapore)

About

80
Publications
14,391
Reads
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883
Citations
Citations since 2016
58 Research Items
824 Citations
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
Introduction
My research directions include data science and visual analytics applied in different domains, particularly, in health informatics, bioinformatics, and drug discovery.
Additional affiliations
February 2017 - July 2018
Institute of High Performance Computing
Position
  • Scientist
July 2015 - January 2017
Duke-NUS Medical School, National University of Singapore
Position
  • Research Associate
August 2012 - July 2015
National University of Singapore
Position
  • Research Associate

Publications

Publications (80)
Article
Full-text available
Radiofrequency (RF) ablation is a good alternative to hepatic resection for treatment of liver tumors. However, accurate needle insertion requires precise hand-eye coordination and is also affected by the difficulty of RF needle navigation. This paper proposes a cooperative surgical robot system, guided by hand gestures and supported by an augmente...
Article
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Biometric recognition can be used to improve gesture-based interfaces by automatically identifying operators. Traditional palm biometric recognition techniques depend on palm appearance features, but these features are not available in an operating theater where gloves are worn. We propose a depth-based solution for palm biometric recognition. Base...
Article
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Background Since protein-DNA interactions are highly essential to diverse biological events, accurately positioning the location of the DNA-binding residues is necessary. This biological issue, however, is currently a challenging task in the age of post-genomic where data on protein sequences have expanded very fast. In this study, we propose iProD...
Article
Background and objective Atrial fibrillation (AF) is the most common form of cardiac rhythm disorder. Early detection of AF can result in a lower risk of stroke, heart failure, systemic thromboembolism, and coronary artery disease. AF detection however is challenging due to the need for specialised equipment and professional technicians. Hand-held...
Chapter
k-NN is a widely used supervised machine learning method in different domains. Despite its simplicity, effectiveness, and robustness, k-NN is limited to the use of the Euclidean distance as the similarity metric, the arbitrarily selected neighborhood size k, the computational challenge from high dimensional data, and the use of the simple majority...
Article
Full-text available
Background: Adaptor proteins play a key role in intercellular signal transduction, and dysfunctional adaptor proteins result in diseases. Understanding its structure is the first step to tackling the associated conditions, spurring ongoing interest in research into adaptor proteins with bioinformatics and computational biology. Our study aims to in...
Article
Non‐classical secreted proteins refer to a group of proteins released into the extracellular environment under the facilitation of different biological transporting pathways apart from the Sec/Tat system. As experimental determination of non‐classical secreted proteins is often costly and requires skilled handling techniques, computational approach...
Article
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Background Promoters, non-coding DNA sequences located at upstream regions of the transcription start site of genes/gene clusters, are essential regulatory elements for the initiation and regulation of transcriptional processes. Furthermore, identifying promoters in DNA sequences and genomes significantly contributes to discovering entire structure...
Article
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Background Herpes zoster (HZ) and associated complications cause significant burden to older people. A HZ vaccination programme was introduced in Aotearoa New Zealand in April 2018 with a single dose vaccine for those aged 65 years and a four-year catch up for 66–80 year-olds. This study aimed to assess the ‘real-world’ effectiveness of the zoster...
Article
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Transcription factors (TFs) play an important role in gene expression and regulation of 3D genome conformation. TFs have ability to bind to specific DNA fragments called enhancers and promoters. Some TFs bind to promoter DNA fragments which are near the transcription initiation site and form complexes that allow polymerase enzymes to bind to initia...
Article
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There is a growing body of literature supporting the utilization of machine learning (ML) to improve diagnosis and prognosis tools of cardiovascular disease. The current study was to investigate the impact that the ML framework may have on the sensitivity of predicting the presence or absence of congenital heart disease (CHD) using fetal echocardio...
Article
Background Given the substantial impact of herpes zoster on health and quality of life, and its considerable economic burden, prevention through vaccination is a priority. We aimed to evaluate the effectiveness of the herpes zoster vaccines (recombinant zoster vaccine [RZV] and zoster vaccine live [ZVL]) against incident herpes zoster and postherpe...
Article
Cancer is one of the most deadly diseases that annually kills millions of people worldwide. The investigation on anticancer medicines has never ceased to seek better and more adaptive agents with fewer side effects. Besides chemically synthetic anticancer compounds, natural products are scientifically proved as a highly potential alternative source...
Article
Bone age is an important index in the measurement of the biological maturity in children. Although many machine learning methods have been developed to classify bone radiographs, a number of limitations like the need for large datasets still exists. In this paper, we propose an efficient method based on convolutional neural networks to automaticall...
Article
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Background: COVID-19 elimination measures, including border closures have been applied in New Zealand. We have modelled the potential effect of vaccination programmes for opening borders. Methods: We used a deterministic age-stratified Susceptible, Exposed, Infectious, Recovered (SEIR) model. We minimised spread by varying the age-stratified vaccin...
Article
Background There is a variety of mortality prediction models for patients in intensive care units (ICU) to guide appropriate clinical management. Advances in machine learning methodologies typically employ classifiers such as Neural Network and Random Forest which are often regarded by healthcare professionals as black boxes. These models often do...
Chapter
Hand pose estimation has recently attracted increasing research interest, especially with the advance of deep learning. Albeit many successes, the current state of research does present some opportunities for improvement of estimation accuracy. This paper presents several image enhancement techniques to embed with existing deep learning architectur...
Chapter
Rehabilitation of the hands is crucial for stroke survivors to regain their ability to perform activities of daily living. Various technologies were explored and found unmatured, expensive and uncomfortable. Existing devices to assist rehabilitation are typically costly, bulky and difficult to set up. Our proposed solution aims to provide an end-to...
Article
Robo-advisors are increasingly popular, with machine learning algorithms taking centre stage for researchers. However, classical financial theories and techniques, such as Constant Rebalancing (CRB) and Modern Portfolio Theory (MPT), can still be relevant by combining them with social media sentiments. In this study, we propose two novel models, na...
Article
Full-text available
Introduction Herpes zoster (HZ) and associated complications inflict substantial morbidity and associated healthcare and socioeconomic burdens. Current treatments are not fully effective, especially among the most vulnerable populations. Two HZ vaccines are available and are part of the national immunisation programmes in many countries. This revie...
Chapter
The increasing importance of human activity recognition in Ambient Assisted Living systems (AAL) has brought a tremendous growth in research efforts in the field. Amongst these, the identification of activities of daily living using sensors available in mobile devices has emerged as one of the most interesting goals for AAL systems. With the develo...
Chapter
Prostate MP-MRI scan is a non-invasive method of detecting early stage prostate cancer which is increasing in popularity. However, this imaging modality requires highly skilled radiologists to interpret the images which incurs significant time and cost. Convolutional neural networks may alleviate the workload of radiologists by discriminating betwe...
Chapter
Warts are skin growths that are caused by the human papillomavirus (HPV) through direct or indirect contact with an object used by a person with the virus. There are different types of warts and different treatment methods accordingly. Of which the cryotherapy method is preferably used to enhance the existing conventional treatment methods. As the...
Chapter
Parkinson’s disease (PD) is a progressive neurological disorder that affects movement of millions of people worldwide. Many methods have been developed to identify and diagnose PD in patients. However, most of these approaches require extensive setup and involve costly equipment such as using depth cameras or devices worn on the body. In this study...
Chapter
Gait patterns of Cerebral Palsy (CP) patients have been used for cluster and classification analysis. Diplegia is the paralysis of one or more body parts which may be caused by CP and may come in various forms. Current clinical practice in gait issue diagnosis relies heavily on observation and is prone to human error. Following previous studies, th...
Chapter
We present our approach in achieving the Quadratic Weighted Kappa (QWK) score of 0.90 on the retinal image dataset from the APTOS 2019 Blindness Detection Kaggle challenge. We analysed various image preprocessing techniques then classified the images with a modified EfficientNet deep learning model. Our image preprocessing techniques helped to brin...
Chapter
Advances in high-content high-throughput fluorescence microscopy have emerged as a powerful tool for several stages of drug discovery process, leading to the identification of a drug candidate with the potential for becoming a marketed drug. This high-content screening (HCS) technology has recently involved the application of machine learning metho...
Article
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As a critical issue in drug development and postmarketing safety surveillance, drug-induced liver injury (DILI) leads to failures in clinical trials as well as retractions of on-market approved drugs. Therefore, it is important to identify DILI compounds in the early-stages through in silico and in vivo studies. It is difficult using conventional s...
Article
Immense amount of high-content image data generated in drug discovery screening requires computationally driven automated analysis. Emergence of advanced machine learning algorithms, like deep learning models, has transformed the interpretation and analysis of imaging data. However, deep learning methods generally require large number of high-quali...
Article
Drug-induced hepatocellular cholestasis leads to altered bile flow. Bile is propelled along the bile canaliculi (BC) by actomyosin contractility, triggered by increased intracellular calcium (Ca²⁺). However, the source of increased intracellular Ca²⁺ and its relationship to transporter activity remains elusive. We identify the source of the intrace...
Article
Full-text available
Background: Pseudouridine modification is most commonly found among various kinds of RNA modification occurred in both prokaryotes and eukaryotes. This biochemical event has been proved to occur in multiple types of RNAs, including rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, gaining a holistic understanding of pseudouridine modification ca...
Article
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Background 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 identification is, therefore, more complicated than other genetic factors. To address this biological issue, several in silico stud...
Article
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Background: 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 with other intracellular-signaling molecules. Many studies determined that the adaptor proteins had been implicated in a variety...
Article
Flavin mono-nucleotides (FMNs) are cofactors that hold responsibility for carrying and transferring electrons in the electron transport chain stage of cellular respiration. Without being facilitated by FMNs, energy production is stagnant due to the interruption in most of the cellular processes. Investigation on FMN's functions, therefore, can gain...
Preprint
Bile canaliculi (BC) are the smallest vessels of the biliary tree. They are formed from the apical surfaces of adjoining hepatocytes, resulting in lumenal conduits for bile flow. Bile is propelled along the BC by hepatocyte contractions that arise from cyclic waves of apico-basal Ca2+, but the source and regulation of Ca2+ has been unclear. We repo...
Article
Full-text available
A novel automated framework is proposed in this paper to address the significant but challenging task of multi-label brain tumor segmentation. Kernel sparse representation, which produces discriminative sparse codes to represent features in a high-dimensional feature space, is the key component of the proposed framework. The graph-cut method is int...
Article
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Multidimensional transfer functions can perform more sophisticated classification of volumetric objects compared to 1-D transfer functions. However, visualizing and manipulating the transfer function space is non-intuitive when its dimension goes beyond 3-D, thus making user interaction difficult. In this paper, we propose to address the multidimen...
Article
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Background Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addres...
Article
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In the Letter 'Unified VLSI architecture for photo core transform used in JPEG XR', the authors proposed a hardware architecture to implement the three elementary 2 x 2 transform operations for the photo core transform used in JPEG XR. However, there are some errors in their implementation, dataflow and reported resources used. In this Letter, we p...
Article
Full-text available
In volume visualization, transfer functions are used to classify the volumetric data and assign optical properties to the voxels. In general, transfer functions are generated in a transfer function space, which is the feature space constructed by data values and properties derived from the data. If volumetric objects have the same or overlapping da...
Conference Paper
Full-text available
This paper presents the architecture and work flow of an intelligent surgical robotic system that we are developing. The robotic surgical system which comprises a cognitive engine is designed to augment and enhance the hand-eye coordination capability of the surgeon during operation in order to achieve the desired outcome and reduce invasiveness. B...
Conference Paper
Full-text available
Traditional surgical planning is challenged by limited spatial information of 2-D medical images or separated planning phases between 3-D model based virtual planning and its in situ registration. This paper presents an augmented surgical planning method with model-section views of an actual patient body and direct augmented interaction to realize...