Phung Anh Nguyen

Taipei Medical University | TMU

Introduction Pancreatic cancer is associated with poor prognosis. Considering the increased global incidence of diabetes cases and that individuals with diabetes are considered a high-risk subpopulation for pancreatic cancer, it is critical to detect the risk of pancreatic cancer within populations of person living = with diabetes. This study aimed...

Importance Ranitidine, the most widely used histamine-2 receptor antagonist (H 2 RA), was withdrawn because of N-nitrosodimethylamine impurity in 2020. Given the worldwide exposure to this drug, the potential risk of cancer development associated with the intake of known carcinogens is an important epidemiological concern. Objective To examine the...

Objectives The objective of this study was to apply machine learning algorithms to predict the risk of ischemic stroke in type 2 diabetes mellitus patients who were prescribed antidiabetic medications. This is an important complication of type 2 diabetes, and developing prediction models can help identify patients at a higher risk of developing it....

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...

The study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospital...

Objectives A vast amount of literature has been conducted for investigating the association of different lunar phases with human health; and it has mixed reviews for association and non-association of diseases with lunar phases. This study investigates the existence of any impact of moon phases on humans by exploring the difference in the rate of o...

Background: Psoriasis (PsO) is a chronic, systemic, immune-mediated disease with multiorgan involvement. Psoriatic arthritis (PsA) is an inflammatory arthritis that is present in 6%-42% of patients with PsO. Approximately 15% of patients with PsO have undiagnosed PsA. Predicting patients with a risk of PsA is crucial for providing them with early...

Background and objective: The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice. Methods:...

The chronic receipt of renin-angiotensin-aldosterone system (RAAS) inhibitors including angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been assumed to be associated with a significant decrease in overall gynecologic cancer risks. This study aimed to investigate the associations of long-term RAAS inhib...

Background: Firm conclusions about whether long-term proton pump inhibitor (PPI) drug use impacts female cancer risk remain controversial. Objective: We aimed to investigate the associations between PPI use and female cancer risks. Methods: A nationwide population-based, nested case-control study was conducted within Taiwan’s Health and Welfare Dat...

A well-established lung-cancer-survival-prediction model that relies on multiple data types, multiple novel machine-learning algorithms, and external testing is absent in the literature. This study aims to address this gap and determine the critical factors of lung cancer survival. We selected non-small-cell lung cancer patients from a retrospectiv...

Objectives The coronavirus disease 2019 pandemic has affected countries around the world since 2020, and an increasing number of people are being infected. The purpose of this research was to use big data and artificial intelligence technology to find key factors associated with the coronavirus disease 2019 infection. The results can be used as a r...

This study established a predictive model for the early detection of micro-progression of pressure injuries (PIs) from the perspective of nurses. An easy and programing-free artificial intelligence modeling tool with professional evaluation capability and it performed independently by nurses was used for this purpose. In the preliminary evaluation,...

BACKGROUND Psoriasis (PsO) is a chronic, systemic, immune-mediated disease with multiorgan involvement. Psoriatic arthritis (PsA) is an inflammatory arthritis that is present in 6%-42% of patients with PsO. Approximately 15% of patients with PsO have undiagnosed PsA. Predicting patients with a risk of PsA is crucial for providing them with early ex...

Importance: More than 1 billion adults have hypertension globally, of whom 70% cannot achieve their hypertension control goal with monotherapy alone. Data are lacking on clinical use patterns of dual combination therapies prescribed to patients who escalate from monotherapy. Objective: To investigate the most common dual combinations prescribed...

Despite previous studies on statins, aspirin, metformin, and angiotensin-converting-enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs), little has been studied about all their possible combinations for chemoprevention against cancers. This study aimed to comprehensively analyze the composite chemopreventive effects of all the combina...

Introduction: Over one billion adults have hypertension globally, of whom 70% cannot achieve hypertension control with monotherapy. Data are lacking on patterns of dual combination therapies prescribed to patients who escalate from monotherapy. Methods: We described dual combination therapy utilization using eleven electronic health record database...

Background Hepatocellular carcinoma (HCC), usually known as hepatoma, is the third leading cause of cancer mortality globally. Early detection of HCC helps in its treatment and increases survival rates. Objective The aim of this study is to develop a deep learning model, using the trend and severity of each medical event from the electronic health...

Purpose: To develop deep learning model (Deep-KOA) that can predict the risk of knee osteoarthritis (KOA) within the next year by using the previous three years nonimage-based electronic medical record (EMR) data. Patients and methods: We randomly selected information of two million patients from the Taiwan National Health Insurance Research Dat...

Background: Over one billion adults have hypertension globally, of whom approximately 70% cannot achieve blood pressure control goal with monotherapy alone. Data are lacking on patterns of dual combination therapies prescribed to patients who escalate from monotherapy in routine practice. Methods: Using eleven electronic health record databases tha...

Immune checkpoint inhibitors (ICIs) have been approved to treat patients with various cancer types, including lung cancer, in many countries. This study aims to investigate the effectiveness and safety of ICIs under different treatment conditions of non-small cell lung cancer patients. A population-based retrospective cohort study was conducted usi...

Levothyroxine is a widely prescribed medication for the treatment of an underactive thyroid. The relationship between levothyroxine use and cancer risk is largely underdetermined. To investigate the magnitude of the possible association between levothyroxine use and cancer risk, this retrospective case‐control study was conducted using Taiwan’s Hea...

Background and Objective : Association rule mining has been adopted to medical fields to discover prescribing patterns or relationships among diseases and/or medications; however, it has generated unreasonable associations among these entities. This study aims to identify the real-world profile of disease-medication (DM) associations using the modi...

Background Existing epidemiological evidence regarding the association between the long-term use of drugs and cancer risk remains controversial. Objective We aimed to have a comprehensive view of the cancer risk of the long-term use of drugs. MethodsA nationwide population-based, nested, case-control study was conducted within the National Health I...

Background Although most current medication error prevention systems are rule-based, these systems may result in alert fatigue because of poor accuracy. Previously, we had developed a machine learning (ML) model based on Taiwan’s local databases (TLD) to address this issue. However, the international transferability of this model is unclear. Objec...

We aimed to develop deep learning models for the prediction of the risk of advanced nonmelanoma skin cancer (NMSC) in Taiwanese adults. We collected the data of 9494 patients from Taiwan National Health Insurance data claim from 1999 to 2013. All patients’ diseases and medications were included in the development of the convolution neural network (...

Background Computerized physician order entry (CPOE) systems are incorporated into clinical decision support systems (CDSSs) to reduce medication errors and improve patient safety. Automatic alerts generated from CDSSs can directly assist physicians in making useful clinical decisions and can help shape prescribing behavior. Multiple studies report...

Purpose: We examined factors associated with health literacy among elders with and without suspected COVID-19 symptoms (S-COVID-19-S). Methods: A cross-sectional study was conducted at outpatient departments of nine hospitals and health centers 14 February−2 March 2020. Self-administered questionnaires were used to assess patient characteristics,...

BACKGROUND Although most current medication error prevention systems are rule-based, these systems may result in alert fatigue because of poor accuracy. Previously, we had developed a machine learning (ML) model based on Taiwan’s local databases (TLD) to address this issue. However, the international transferability of this model is unclear. OBJEC...

Statins have shown beneficial treatment as chemotherapy and target‐therapy for lung cancer. This study aims to investigate the effectiveness of statins in combination with epidermal growth factor receptor‐ tyrosine kinase inhibitors (EGFR‐TKIs) therapy on resistance and mortality of lung cancer patients. A population‐based cohort study was conducte...

We developed a deep learning approach for accurate prediction of PCA patients one year earlier with minimal features from electronic health records. The area under the receiver operating curve for prediction of PCA was 0.94. Moreover, the sensitivity and specificity of CNN were 0.87 and 0.88, respectively.

BACKGROUND Existing epidemiological evidence regarding the association between the long-term use of drugs and cancer risk remains controversial. OBJECTIVE We aimed to have a comprehensive view of the cancer risk of the long-term use of drugs. METHODS A nationwide population-based, nested, case-control study was conducted within the National Healt...

Purpose: Proton pump inhibitors (PPIs), one of the most widely used medications, are commonly used to suppress several acid-related upper gastrointestinal disorders. Acid-suppressing medication use could be associated with increased risk of community-acquired pneumonia (CAP), although the results of clinical studies have been conflicting. Data so...

BACKGROUND Hepatocellular carcinoma (HCC), usually known as hepatoma, is the third leading cause of cancer mortality globally. Early detection of HCC helps in its treatment and increases survival rates. OBJECTIVE The aim of this study is to develop a deep learning model, using the trend and severity of each medical event from the electronic health...

BACKGROUND Computerized physician order entry (CPOE) systems are incorporated into clinical decision support systems (CDSSs) to reduce medication errors and improve patient safety. Automatic alerts generated from CDSSs can directly assist physicians in making useful clinical decisions and can help shape prescribing behavior. Multiple studies report...

BACKGROUND The automatic segmentation of skin lesions has been reported using the data of dermoscopic images. It is, however, not applicable to real-time detection using a smartphone. OBJECTIVE This study aims to examine a deep learning model for detecting and localizing positions of the mole on the captured images to precisely extract the crop im...

Given that advanced melanoma has a poor prognosis, earlier detection is essential.1 Recently, deep learning (DL) models have shown promise in aiding diagnosis of melanoma.2,3 However, these models only consider images but not complementary clinical information; and are mainly for diagnostic purpose, rather than screening.

Antidiabetic medications are commonly used around the world, but their safety is still unclear. The aim of this study was to investigate whether long-term use of insulin and oral antidiabetic medications is associated with cancer risk. We conducted a well-designed case–control study using 12 years of data from Taiwan's National Health Insurance Res...

We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal cancer in Taiwanese adults. We collected data of 58152 patients from the Taiwan National Health Insurance database from 1999 to 2013. All patients' comorbidities and medications history were included in the development of the convolution neural network (...

The demand for AI to improve patients outcome has been increased; we, therefore, aim to establish the diagnostic values of AI in diabetic retinopathy by pooling the published studies of deep learning on this subject. A total of eight studies included which evaluated deep learning in a total of 706,922 retinal images. The overall pooled area under r...

Résumé Objectif Aucune conclusion définitive n’a été tirée à ce jour concernant le risque de cancer lié aux traitements de la goutte administrés à court et long terme. Cette étude avait pour objectif d’évaluer l’association entre l’utilisation des traitements antigoutteux et le risque de cancer. Méthodes Nous avons mené une étude rétrospective lon...

Background and objective: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for prevention, early diagnosis and treatment. We aimed to develop a machine learning model to predict FLD th...

Objective: Firm conclusion about whether short and long-term gout medications use has an impact on cancer risk remain inconclusive. The aim of this study was to investigate the association between gout drugs use and risk of cancer. Methods: We conducted a retrospective longitudinal population-based case-control study in Taiwan. Cases were identi...

PurposeTo investigate whether the use of levothyroxine was associated with breast cancer risk. Methods We conducted a population-based case–control study in Taiwan. Cases consisted of all patients who were aged 20 years and older, and had a first-time diagnosis of breast cancer for the period between 2001 and 2011. The controls were matched to the...

Epidermal growth factor receptor (EGFR) mutation is prevalently expressed in lung adenocarcinoma cases and acts as one of the major driving oncogenes. EGFR tyrosine kinase inhibitors (TKIs) have been used in patients with EGFR-mutant as an effective targeted therapy in lung adenocarcinoma, but drug resistance and tumor recurrence inevitably occurs....

Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and diseases. The study aims to identify and evaluate the meaningful associations between TCM herbs and breast cancer by using the association rule mining (ARM) techniques. We employed the ARM techniques...

Background: Parkinson's disease (PD) is a progressive disorder of the central nervous system. The prevalence of PD varies considerably by age group; it has a higher prevalence in patients aged 60 years and more. Several studies have shown that statin, a cholesterol-lowering medication, reduces the risk of developing PD, but evidence for this is so...

Objective: Birth month and climate impact lifetime disease risk, while the underlying exposures remain largely elusive. We seek to uncover distal risk factors underlying these relationships by probing the relationship between global exposure variance and disease risk variance by birth season. Material and methods: This study utilizes electronic...

Cancer is a multifactorial disease, and imbalances of the immune response and sex-associated features are considered risk factors for certain types of cancer. The present study aimed to assess whether ankylosing spondylitis (AS), an immune disorder that predominantly affects young adult men, is associated with an increased risk of cancer. Using the...

Background Some of the thyroid disorders (TD) and Myasthenia gravis (MG) are autoimmune related disease. The purpose of the study to evaluate the relationship of MG with all morphological and functional thyroid disorders. Methods: We constructed a population-based cohort study during the period from January 2000-December 2002 by using reimbursement...

Objective Rapid change in health information technology system had dramatically increased health data accumulated. We aimed to develop an online informatics tool in order to evaluate the risk of drugs for cancer by utilizing medical big data. Data SourceWe use the Taiwan’s National Health Insurance Database that has provided a huge data which cover...

Objectives: Medication non-adherence caused by forgetting and delays has serious health implications and causes substantial expenses to patients, healthcare providers, and insurance companies. We assessed the effectiveness of a personalized medication management platform (PMMP) for improving medication adherence, self-management medication, and re...

Objective: Cancer is the primary disease responsible for death and disability worldwide. Currently, prevention and early detection represents the best hope for cure. Knowing the expected diseases that occur with a particular cancer in advance could lead to physicians being able to better tailor their treatment for cancer. The aim of this study was...

Purpose: Medication errors such as potential inappropriate prescriptions would induce serious adverse drug events to patients. Information technology has the ability to prevent medication errors; however, the pharmacology of traditional Chinese medicine (TCM) is not as clear as in western medicine. The aim of this study was to apply the appropriat...

Background: Electronic medical records (EMRs) contain vast amounts of data that is of great interest to physicians, clinical researchers, and medial policy makers. As the size, complexity, and accessibility of EMRs grow, the ability to extract meaningful information from them has become an increasingly important problem to solve. Methods: We dev...

Recent discussions have focused on using health information technology (HIT) to support goals related to universal healthcare delivery. These discussions have generally not reflected on the experience of countries with a large amount of experience using HIT to support universal healthcare on a national level. HIT was compared globally by using data...

Many developing countries suffer a scarcity of trained clinicians, which are usually concentrated in urban centers, leaving large rural populations essentially underserved. Technology adoption could offer new opportunities for patients′ benefit in term of costs, better care and in turn, better outcomes. 1 Telemedicine is a promising tool to amelior...