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197
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Introduction
Khanh Lee is an Associate Professor with the Professional Master Program in Artificial Intelligence in Medicine, Taipei Medical University, Taiwan. He received his MS and Ph.D. degree in the Department of Computer Science and Engineering, Yuan Ze University, Taiwan. After obtaining his Ph.D. degree, he was a Research Fellow at the School of Humanities, Nanyang Technological University, Singapore. His research interests are Artificial Intelligence, Medical Imaging, and Bioinformatics.
Current institution
Additional affiliations
August 2019 - present
August 2019 - present
August 2018 - August 2019
Education
February 2014 - January 2018
February 2012 - January 2014
September 2005 - January 2010
Publications
Publications (197)
The tumor immune microenvironment (TME) influences cancer progression and treatment. RNA-Seq has identified six immune subtypes: Wound Healing (WH, C1), IFN-γ Dominant (IFNG, C2), Inflammatory (INF, C3), Lymphocyte Depleted (LD, C4), Immunologically Quiet (IQ, C5), and TGF-β Dominant (TGFb, C6). This study uses a Convolutional Neural Network (CNN)...
Background: Hepatocellular carcinoma (HCC) is a global health challenge, ranking sixth in incidence and third in cancer-related mortality. Microvascular invasion (MVI) is a crucial prognostic marker influencing recurrence rates and survival. Accurate preoperative MVI detection can guide surgical planning but is limited by invasive histopathological...
Background: Advances in medical image segmentation have raised debate about the practical performance of the latest architectures and CNN-based approaches. Recent studies have demonstrated that CNN-based architectures maintain competitive performance compared to newer architectural paradigms despite limited task-specific validation.
Method: Due t...
Abstract
Background
Epidermal growth factor receptor (EGFR) mutations play a pivotal role in guiding targeted therapy for lung cancer, making their accurate detection essential for personalized treatment. Recently, artificial intelligence (AI) has emerged as a promising tool for identifying EGFR mutation status from digital pathology images. This s...
Background
Pan-cancer analysis offers a holistic perspective on cancer, spanning 33 types and over 11,000 tumor samples from The Cancer Genome Atlas (TCGA). This analysis provides key insights into molecular features shared across cancers and aids in identifying immune subtypes, which are critical for developing personalized immunotherapies. Six di...
Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past decade, the emergence of deep learning (DL) has greatly contributed to addressing DRP challenges. Notably, the prediction of DRP for cancer cell lines benefits significantly from data availability for model development. However, an effective predictive...
This study explores radiomics in the broader context of liver disease research, an interdisciplinary field bridging medical imaging, oncology, and data science. It begins with an introduction to data analysis techniques, from foundational methods like descriptive statistics, comparative and regression analysis, and survival analysis, to advanced ap...
Objectives
Pediatric elbow fractures are a common injury among children. Recent advancements in artificial intelligence (AI), particularly deep learning (DL), have shown promise in diagnosing these fractures. This study systematically evaluated the performance of DL models in detecting pediatric elbow fractures.
Materials and methods
A comprehensi...
Protein ubiquitination is a crucial post-translational modification
involving the attachment of ubiquitin molecules to proteins, forming ubiquitin-
protein complexes. This modification plays a pivotal role in various biological
processes, including protein decomposition, regulation of enzymatic activity,
modulation of interactions, cell cycle reg...
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) comprising NSCLC patients, 420 patients and 516 patients for Lung 1 training and Lung 2 testing, res...
Background
Meningiomas are typically found in adults, with an average diagnosis age of 66. However, they can occur in children, presenting unique clinical and immunohistochemical characteristics. This report explores a rare pediatric case of anaplastic meningioma, highlighting the diagnostic and treatment challenges involved.
Clinical finding, lab...
The integration of artificial intelligence (AI) and genomics is revolutionizing cancer drug discovery by enabling personalized and effective therapies. This review explores the application of AI technologies, such as deep learning and data analytics, in transforming the identification, design, and evaluation of cancer drugs. AI plays a pivotal role...
SNARE proteins play a pivotal role in membrane fusion and various cellular processes. Accurate identification of SNARE proteins is crucial for elucidating their functions in both health and disease contexts. This chapter presents a novel approach employing multiscan convolutional neural networks (CNNs) combined with position-specific scoring matrix...
Accurate prediction of RNA modifications holds profound implications for elucidating RNA function and mechanism, with potential applications in drug development. Here, the RNA-ModX presents a highly precise predictive model designed to forecast post-transcriptional RNA modifications, complemented by a user-friendly web application tailored for seam...
The rapid evolution of artificial intelligence (AI) is redefining biomedicine, placing itself at the forefront of groundbreaking discoveries in molecular biology, genomics, drug discovery, diagnostics, and beyond [...]
Tight junction proteins are a crucial type of protein in the structure of cell membranes in multicellular organizations, such as the intestinal epithelium, urinary tract epithelium, and other tissues. They hold adjacent cells tightly together, forming a barrier that prevents the passage of fluids and other molecules between cells. Tight junctions m...
Accurate quantification of intraoperative blood loss is crucial for enhancing patient safety and the success rate of surgeries. Traditional estimation techniques, mainly reliant on visual assessments, are prone to significant inaccuracies due to their subjective nature. This study introduces MDCare, an innovative deep learning-integrated system des...
Protein ubiquitination is a critical post-translational modification (PTM) that participates in a wide range of biological processes and plays a pivotal role in the regulation of physiological mechanisms and disease states. Despite substantial efforts leading to the development of various ubiquitination site prediction tools across multiple species...
Protein SUMOylation is one of the most important post-translational modifications in Eukaryotes species and plays significant roles in many biological processes. The mechanism underlined the SUMOylation process will be an important cause leading to many common serious diseases, such as breast cancer, cardiac, Parkinson’s, Alzheimer’s disease, etc....
Background and Aim
The Rome IV criteria, the standard for diagnosing functional constipation (FC), deem the Bristol Stool Scale (BSS) unsuitable for assessing stool consistency in young children. Hence, the Brussels Infant and Toddler Stool Scale (BITSS) was developed. We aimed to validate and test the reliability of BITSS for hard stools and FC am...
Purpose
To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status based on embryonic characteristics and clinical data.
Methods
This retrospective study utilized a dataset of 1908 blastocyst embryos. The dataset includes ploidy status, morphokinetic features, morpho...
Introduction:
This review explores the transformative impact of machine learning (ML) on carcinogenicity prediction within drug development. It discusses the historical context and recent advancements, emphasizing the significance of ML methodologies in overcoming challenges related to data interpretation, ethical considerations, and regulatory ac...
𝑁4-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing to epigenetic regulation.
It exists in various genomes, including the Rosaceae family encompassing significant fruit crops like apples,
cherries, and roses. Previous investigations have examined the distribution and functional implications of
4mC sites within the Rosa...
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 harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics in conjunction with clinical data, focusing on 3-year progres...
Background
Constipation is prevalent worldwide, significantly increasing healthcare costs and diminishing the quality of life in children affected. Current studies have yielded mixed results regarding the factors associated with constipation, and mainly focusing on patients outside of Asia. Moreover, most of these studies lack focus on the paediatr...
Artificial Intelligence (AI) is revolutionizing hepatitis management through Machine Learning (ML) and Deep Learning (DL). These technologies enable risk prediction, diagnosis, and personalized screening protocols, enhancing the efficiency of healthcare delivery. ML algorithms analyze patient data to identify individuals at high risk of infection,...
In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these lim...
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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 role in shaping consumers’ initial impressions and influencing their decision to purchase a spotted melon. However, accurately determining the s...
The role of the IFI6 gene has been described in several cancers, but its involvement in esophageal cancer (ESCA) remains unclear. This study aimed to identify novel prognostic indicators for ESCA-targeted therapy by investigating IFI6’s expression, epigenetic mechanisms, and signaling activities. We utilized public data from the Gene Expression Omn...
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 pediatric distal forearm fractures, guided by the AO Foundation/Orthopaedic Trauma Association (AO/ATO) classification system for pediatric...
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 modalities, and the evolution of cellular physiological and developmental processes. However, the experimental delineation of mRNA subcellular loca...
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 incubation, which minimizes environmental changes in the embryo culture process. TLS also significantly advances predicting embryo quality, a cruci...
DNA N⁶-methyladenosine (6 mA) modification carries significant epigenetic information and plays a pivotal role in biological functions, thereby profoundly impacting human development. Precise and reliable detection of 6 mA sites is integral to understanding the mechanisms underpinning DNA modification. The present methods, primarily experimental, u...
Gastric cancer (GC) represents a significant global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide. Despite recent advancements in GC treatment, the five-year survival rate for advanced-stage GC patients remains low. Consequently, there is an urgent need to identify novel dr...
In recent years, many mammographic image analysis methods have been introduced for improving cancer classification tasks. Two major issues of mammogram classification tasks are leveraging multi-view mammographic information and class-imbalance handling. In the first problem, many multi-view methods have been released for concatenating features of t...
The ingested foreign body is a very unusual etiology of liver abscess. This clinical scenario is infrequently reported in the literature. A 66-year-old male patient presented to the hospital because of abdominal pain along with 7 days of right upper quadrant pain and intermittent low-grade fever. He was living in an epidemiological area of Fasciola...
Background: Determining the O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, which is a predictor of response to standard radiotherapy treatment in patients with glioblastoma (GBM), remains an invasive and time-consuming process. Magnetic resonance imaging (MRI)-based radiomics studies have used machine learning models as...
Protein crystallization is crucial for biology, but the steps involved are complex and demanding in terms of external factors and internal structure. To save on experimental costs and time, the tendency of proteins to crystallize can be initially determined and screened by modeling. As a result, this study created a new pipeline aimed at using prot...
BACKGROUND
The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.
OBJECTIVE
This study aims to develop a personalized predictive model, utilizing artificial intelligence, to assess the 5-year and 10-year dementia risk among patients with Type 2 Diabetes Mellitus (T2DM) who...
Background
The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.
Objective
This study aimed to develop a personalized predictive model, using artificial intelligence, to assess the 5-year and 10-year dementia risk among patients with type 2 diabetes mellitus (T2DM) who are...
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 rind. In this study, we presented a novel approach for predicting melon sweetness levels using features extracted from segmented rind images and...
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 diagnosis is one of them. The DNA methylation of CpG island sequences found in the promoter regions of tumor suppressor genes has recently receiv...
Simple Summary
People with glioblastoma (GBM) universally have poor survival despite undergoing aggressive treatments. In this study, we aimed to determine genetic biomarkers of GBM that exhibit prognostic implications and examine their role in the tumor microenvironment. To this end, we performed differential gene expression analysis in three inde...
Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecular tests, the advent of robust and scalable techniques for nucleic acid analysis has revolutionized biological research and medicinal practice in lung cancer treatment. In response to the demands for...
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 function of almost all proteins. They are essential for a diverse and well-functioning proteome and can integrate metabolism with physiological...
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 survival in GBM patients and validate it in LGG patients. From each patient's 704 MRI-based radiomics features, we chose seventeen optimal radiomi...
In recent years, the rapid growth of biological data has increased interest in using bioinformatics to analyze and interpret this data. Proteomics, which studies the structure, function, and interactions of proteins, is a crucial area of bioinformatics. Using natural language processing (NLP) techniques in proteomics is an emerging field that combi...
Coronary artery vasospasm (CVS), an uncommon cause of acute chest pain, can be provoked by vasoconstriction-induced medications. Misoprostol, a prostaglandin analog, is a safe medication to terminate a pregnancy. However, misoprostol can cause coronary artery vasospasm due to vasoconstrictor properties, leading to acute myocardial infarction with n...
https://www.frontiersin.org/articles/10.3389/fcvm.2023.1115358/full#supplementary-material.
Possible drug–food constituent interactions (DFIs) could change the intended efficiency of particular therapeutics in medical practice. The increasing number of multiple-drug prescriptions leads to the rise of drug–drug interactions (DDIs) and DFIs. These adverse interactions lead to other implications, e.g., the decline in medicament’s effect, the...
Rationale and objectives:
Recent advancements in artificial intelligence (AI) render a substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction in non-small cell lung cancer (NSCLC). We aimed to evaluate the performance and quality of AI algorithms that use radiomics features in predicting EGFR mutation status in...
Background
AFE is a rare obstetric complication with high mortality. Besides standard treatment, veno-arterial extracorporeal membrane oxygenation (VA-ECMO) can be used as an alternative treatment.
Case
A 39-year-old female G2P2 came to hospital due to a bleeding placenta previa at 37 weeks and 5 days of gestation. Dexamethasone was used twice in...
Background
The implantation of artificial chordae, a minimally invasive mitral valve repair technique, has been demonstrated to be safe and effective; however, the overall outcome of this technique remains inconsistent due to a lack of standardized protocols and practical challenges. Our study aims to midterm outcomes of mitral valve repair using a...
Background
Cardiac surgeries in situs inversus totalis (SIT), the transposition of all thoracic and abdominal organs through the midsagittal plane, are challenging due to unusual anatomies and limited data.
Case
A 52-year-old female without significant past medical history presented to our institute with palpitations and dyspnea on exertion. She w...
Background
Electrical storm (ES) is a life-threatening complication in 10-20% of patients with an Implantable Cardioverter Defibrillator (ICD). Anti-arrhythmic drugs (AAD) have complications despite being proven in OPTIC and ARREST to prevent ES.
Case
A 47-year-old male patient with an ICD due to heart failure came to the hospital complaining of a...
Background
Coronary artery vasospasm (CAS) is a rare acute myocardial infarction (AMI) that Misoprostol can induce. This condition may cause severe complications, especially in a high cardiovascular risk patient.
Case
A 42-year-old female, G5P3, presented to the emergency room with acute severe left-sided chest pain, dyspnea, and nausea. Her medic...
Asian children are increasingly being diagnosed with type 1 diabetes (T1D) or type 2 diabetes (T2D), and the presence of coexisting islet autoimmune antibodies complicate diagnosis. Here, we aimed to determine the prevalence of islet cell autoantibodies (ICAs) and glutamic acid decarboxylase 65 autoantibodies (GADAs) in children with T1D versus T2D...
Lung adenocarcinoma (LUAD) is the most prevalent lung cancer and one of the leading causes of death. Previous research found a link between LUAD and Aldehyde Dehydrogenase 2 (ALDH2), a member of aldehyde dehydrogenase gene (ALDH) superfamily. In this study, we identified additional useful prognostic markers for early LUAD identification and targeti...
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 scan images of one cancer tumor in one specific organ also be utilized for overall survival prediction in different types of cancers in diff...
Anticancer peptides (ACPs) are the types of peptides that have been demonstrated to have anticancer activities. Using ACPs to prevent cancer could be a viable alternative to conventional cancer treatments because they are safer and display higher selectivity. Due to ACP identification being highly lab-limited, expensive and lengthy, a computational...
Questions
Questions (4)
Dear researchers,
I intend to submit a manuscript to Nucleic Acid Research (NAR) web server issue 2018. I checked the information from NAR website and knew that we need to send the one page summary to the editor first, then we'll submit the full manuscript later after approving from the editor. However I haven't do that before, could anyone who had experiences can give me some examples about that. Or show me which templates I can use, now I do not know which things I need to include in only one page.
Thank you very much,
Khanh Lee
Like the title, anyone could suggest me some quality conferences in bioinformatics and computational biology field hosted before Feb 2018?
Thanks a lot!
Dear all,
I have some publications with the co-authors this year. When I tried to search them in the google scholar, I found them but my name isn't in the author list (only the other authors). You can check it in the link or the figure with my publication papers.
So, could anyone can help me to solve this case. I would like to display my name in some my publication citations.
Thank you and Best regards,
N.Q. Khanh Le
I'm trying to generate PSSM profiles from fasta files with PSI-BLAST and nr database, but it took around 10 minutes for 1 file. If I have many fasta files, it will take a lot of time.
So any suggestions for reducing the time or we have way to reduce nr database?
Thank you,
Khanh Le
