
Hsuan-Chia YangTaipei Medical University | TMU · Graduate institute of biomedical informatcs
Hsuan-Chia Yang
Doctor of Philosophy
About
133
Publications
39,820
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
2,816
Citations
Introduction
I am an associate Professor at the Graduate Institute of Biomedical Informatics, Taipei Medical University, Taiwan. My fields of expertise including Medical Big Data Analysis, Clinical Decision Support Systems, Pharmacoepidemiology, and Pharmacy. We aim to leverage artificial intelligence to reduce medication errors and enhance drug safety. Additionally, we investigate the relationships between long-term medication use and cancer to develop strategies for chemoprevention.
Additional affiliations
May 2019 - January 2023
Education
September 2012 - January 2017
September 2008 - August 2010
September 2000 - June 2004
Publications
Publications (133)
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...
For locally advanced head and neck squamous cell carcinoma (HNSCC), therapeutic decisions depend on comorbidity or age. We estimated the treatment outcomes of patients with different Charlson comorbidity index (CCI) scores and ages to determine whether aggressive treatment improves survival.Data from the Taiwan National Health Insurance and cancer...
Pancreatic cancer is among the deadliest cancers, with a grim prognosis despite advances in treatment. We conducted a population‐based case–control study from Taiwan, linking Health and Welfare Data Science Center data to the Taiwan Cancer Registry, which offers a promising strategy for its treatment through drug repurposing. The study aims to iden...
Dialysis patients often have inadequate health literacy, affecting self-care and outcomes. This study used LINE app to provide personalized health education to Taiwanese dialysis patients and collected physiological data via wearables. While physical activity levels remained unchanged, participants’ disease literacy significantly improved post-inte...
Objective
The objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources.
Methods
TMUCRD was developed by integrating EHRs from three affilia...
[This corrects the article DOI: 10.1371/journal.pone.0296939.].
[Background]
The completeness of adverse event (AE) reports, crucial for assessing putative causal relationships, is measured using the vigiGrade completeness score in VigiBase, the World Health Organization global database of reported potential AEs. Malaysian reports have surpassed the global average score (approximately 0.44), achieving a 5-year...
Imagine having a knowledge graph that can extract medical health knowledge related to patient diagnosis solutions and treatments from thousands of research papers, distilled using machine learning techniques in healthcare applications. Medical doctors can quickly determine treatments and medications for urgent patients, while researchers can discov...
Since 2020, the COVID-19 epidemic has changed our lives in healthcare behaviors. Forced to wear masks influenced doctor-patient interaction perceptions truly, thus, to build a satisfying relationship is not just empathize with facial expressions. The voice becomes more important for the sake of conquering the burden of masks. Hence, verbal and non-...
Good nonverbal communication between doctor and patient is essential for achieving a successful and therapeutic doctor-patient relationship. Increasing evidence has shown that nonverbal communication mimicry, particularly facial mimicry, where one mirrors another’s facial expressions, is linked to empathy and emotion recognition. Empathy is also th...
Among the elderly, hypertension remains one of the prevalent health conditions, which requires monitoring and intervention strategies. Nevertheless, regular reporting of blood pressure (BP) from these individuals still poses multiple challenges. However, most people own cell phone and are engaged in phone conversations daily. Here, we propose an ad...
Background
Previous studies have identified COVID-19 risk factors, such as age and chronic health conditions, linked to severe outcomes and mortality. However, accurately predicting severe illness in COVID-19 patients remains challenging, lacking precise methods.
Objective
This study aimed to leverage clinical real-world data and multiple machine-...
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...
The International Classification of Diseases (ICD) code is a diagnostic classification standard that is frequently used as a referencing system in healthcare and insurance. However, it takes time and effort to find and use the right diagnosis code based on a patient’s medical records. In response, deep learning (DL) methods have been developed to a...
BACKGROUND
The completeness of adverse event (AE) reports is crucial for assessing putative causal relationships. Little information is known about the underlying factors contributing to reports’ completeness. Malaysian reports surpass the global average vigiGrade completeness score (~0.44), approaching the well-documented benchmark (0.80) with a r...
Background:
Alerts in computerized physician order entry (CPOE) systems can improve patient safety. However, alerts in rule-based systems cannot be customized based on individual patient or user characteristics. This limitation can lead to the presentation of irrelevant alerts and subsequent alert fatigue.
Objective:
We used machine learning app...
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...
Objective:
The popularity of the "bring your own device (BYOD)" concept has grown in recent years, and its application has extended to the healthcare field. This study was aimed at examining nurses' acceptance of a BYOD-supported system after a 9-month implementation period.
Methods:
We used the technology acceptance model to develop and validat...
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...
Background
Several epidemiological studies have shown that psoriasis increases the risk of developing atrial fibrillation but evidence of this is still scarce.
Aims
Our objective was to systematically review, synthesise and critique the epidemiological studies that provided information about the relationship between psoriasis and atrial fibrillati...
Proton pump inhibitors (PPIs) are used for maintaining or improving gastric problems. Evidence from observational studies indicates that PPI therapy is associated with an increased risk of gastric cancer. However, the evidence for PPIs increasing the risk of gastric cancer is still being debated. Therefore, we aimed to investigate whether long-term...
As the obesity rate continues to increase persistently, there is an urgent need to develop an effective weight loss management strategy. Nowadays, the development of artificial intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offers prof...
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...
Currently, the International Classification of Diseases (ICD) codes are being used to improve clinical, financial, and administrative performance. Inaccurate ICD coding can lower the quality of care, and delay or prevent reimbursement. However, selecting the appropriate ICD code from a patient’s clinical history is time-consuming and requires exper...
Background and Objective
: Social media sentiment analysis based on Twitter data can facilitate real-time monitoring of COVID-19 vaccine-related concerns. Thus, the governments can adopt proactive measures to address misinformation and inappropriate behaviors surrounding the COVID-19 vaccine, threatening the success of the national vaccination camp...
A clinical decision support system (CDSS) informs or generates medical recommendations for healthcare practitioners. An alert is the most common way for a CDSS to interact with practitioners. Research about alerts in CDSS has proliferated over the past ten years. The research trend is ongoing with new emerging terms and focus. Bibliometric analysis...
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...
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...
[This corrects the article DOI: 10.2196/26256.].
Background and objective:
Logical Observation Identifiers Names and Codes (LOINC) is a universal standard for identifying laboratory tests and clinical observations. It facilitates a smooth information exchange between hospitals, locally and internationally. Although it offers immense benefits for patient care, LOINC coding is complex, resource-in...
Background:
Artificial intelligence approaches can integrate complex features and can be used to predict a patient's risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions.
Objective:
The aim of this study was to use electronic medical records to prescreen patients who are at risk of de...
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...
Laboratory tests are performed to make effective clinical decisions. However, inappropriate laboratory test ordering hampers patient care and increases financial burden for healthcare. An automated laboratory test recommendation system can provide rapid and appropriate test selection, potentially improving the workflow to help physicians spend more...
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:
The Coronavirus Disease 2019 (COVID-2019) outbreak has spread rapidly and hospitals are overwhelmed with COVID-19 patients. While using swabs from patients is the main way for detecting coronavirus, analyzing chest images could offer an alternative to hospitals where healthcare personnel and testing kits are scarce. Deep learning, in p...
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...
UNSTRUCTURED
We propose the idea of using an open dataset of doctor-patient interactions to develop artificial empathy based on facial emotion recognition. Facial emotion recognition allows a doctor to analyze patient emotions so they can reach out the patient through empathic care. However, face recognition datasets are often difficult to acquire...
We propose the idea of using an open data set of doctor-patient interactions to develop artificial empathy based on facial emotion recognition. Facial emotion recognition allows a doctor to analyze patients' emotions, so that they can reach out to their patients through empathic care. However, face recognition data sets are often difficult to acqui...
Background
After two months of implementing a partial lockdown, the Indonesian government had announced the “New Normal” policy to prevent a further economic crash in the country. This policy received many critics, as Indonesia still experiencing a fluctuated number of infected cases. Understanding public perception through effective risk communica...
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...
Coronavirus disease 2019 (COVID-19) has already raised serious concern globally as the number of confirmed or suspected cases have increased rapidly. Epidemiological studies reported that obesity is associated with a higher rate of mortality in patients with COVID-19. Yet, to our knowledge, there is no comprehensive systematic review and meta-analy...
BACKGROUND
As the obesity rate continues to rise persistently, there is an urgent need to develop an effective weight-loss management strategy. Nowadays, the development of Artificial Intelligence (AI) and cognitive technologies coupled with the rapid spread of messaging platforms and mobile technology with easier access to internet technology offe...
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
Artificial intelligence can integrate complex features and may be used to predict the risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions.
OBJECTIVE
Using electronic medical records to pre-screening patient’s risk for developing lung cancer.
METHODS
Two million participants...
Coronavirus disease 2019 (COVID-19) characterized by
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created serious
concerns about its potential adverse effects. There are limited data on clinical,
radiological, and neonatal outcomes of pregnant women with COVID-19 pneumonia.
This study aimed to assess clinical manifestations and...
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
Laboratory tests are considered an essential part of patient safety as patients’ screening, diagnosis, and follow-up are solely based on laboratory tests. Diagnosis of patients could be wrong, missed, or delayed if laboratory tests are performed erroneously. However, recognizing the value of correct laboratory test ordering remains under...
BACKGROUND
Laboratory tests are considered an essential part of patient safety as patients’ screening, diagnosis, and follow-up are solely based on laboratory tests. Diagnosis of patients could be wrong, missed, or delayed if laboratory tests are performed erroneously. However, recognizing the value of correct laboratory test ordering remains under...
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 conducted a study to evaluate the algorithms based on deep learning to automatically diagnosis of GON from digital fundus images. A systematic articles search was conducted in PubMed, EMBASE, Google Scholar for the study that investigated the performance of deep learning algorithms for the detection of GON. A total of eight studies were included...
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
The COVID-19 outbreak has spread rapidly and hospitals are overwhelmed with COVID-19 patients. While analysis of nasal and throat swabs from patients is the main way to detect COVID-19, analyzing chest images could offer an alternative method to hospitals, where health care personnel and testing kits are scarce. Deep learning (DL), in pa...
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...