Ya-Han Hu

• PhD
• Professor (Full) at National Central University

Mining association rules with multiple minimum supports is an important generalization of the association-rule-mining problem, which was recently proposed by Liu et al. Instead of setting a single minimum support threshold for all items, they allow users to specify multiple minimum supports to reflect the natures of the items, and an Apriori-based...

Sequential pattern mining is an important data-mining method for determining time-related behavior in sequence databases. The information obtained from sequential pattern mining can be used in marketing, medical records, sales analysis, and so on. Existing methods only focus on the concept of frequency because of the assumption that sequences' beha...

RFM analysis and market basket analysis (i.e., frequent pattern mining) are two most important tasks in database marketing. Based on customers’ historical purchasing behavior, RFM analysis can identify a valuable customer group, while market basket analysis can find interesting purchasing patterns. Previous studies reveal that recency, frequency an...

With the evolving realm of news propagation and the surge in social media usage, detecting and combatting fake news has become an increasingly important issue. Currently, fake news detection employs three main feature categories: news text, social context, and news images. However, most studies emphasize just one, while only a limited number incorp...

The rise of social media has amplified online sharing, necessitating businesses to comprehend public sentiment. Traditional sentiment analysis struggles with sarcasm detection and class imbalance. To address this, we introduce Synthetic Ensemble Oversampling methods (SEO) that effectively leverage the strengths of various oversampling algorithms. B...

Purpose Although prior research has employed various variables to predict player churn, the dynamic evolution of the behavioral patterns of players has received limited attention. In this study, churn prediction models are developed by incorporating the progress level, in-game purchase, social interaction, behavioral pattern and behavioral variabil...

Background Missing values in datasets present significant challenges for data analysis, particularly in the medical field where data accuracy is crucial for patient diagnosis and treatment. Although MissForest (MF) has demonstrated efficacy in imputation research and recursive feature elimination (RFE) has proven effective in feature selection, the...

Background Electronic medical records store extensive patient data and serve as a comprehensive repository, including textual medical records like surgical and imaging reports. Their utility in clinical decision support systems is substantial, but the widespread use of ambiguous and unstandardized abbreviations in clinical documents poses challenge...

Hotel recommender systems are crucial tools that assist tourists in filtering through extraneous hotel information, ensuring they find accommodations that align with their preferences. These systems predominantly employ content-based filtering (CBF) and collaborative filtering (CF), including user-based CF (UCF) and item-based CF (ICF), as their co...

Research shows that the excessive image interpretation can lead to errors in radiologists’ interpretations. Therefore, if a decision-making system can be introduced to assist radiologists in generating image reports and accurately identifying lesions holds significant importance. This study utilizes Magnetic Resonance (MR) images of the liver as re...

Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and prioritizing injuries and illnesses on the frontlines of the emergency room. This study aims to create an...

Background The prevalence of violence in acute psychiatric wards is a critical concern. According to a meta-analysis investigating violence in psychiatric inpatient units, researchers estimated that approximately 17% of inpatients commit one or more acts of violence during their stay. Inpatient violence negatively affects health-care providers and...

The demand for medical services has been increasing yearly in aging countries. Medical institutions must hire a large number of staff members to provide efficient and effective health-care services. Because of high workload and pressure, high turnover rates exist among health-care staff members, especially those in nonurban areas, which are charact...

Background Timely detection of atrial fibrillation (AF) after stroke is highly clinically relevant, aiding decisions on the optimal strategies for secondary prevention of stroke. In the context of limited medical resources, it is crucial to set the right priorities of extended heart rhythm monitoring by stratifying patients into different risk grou...

Opinion mining focuses on extracting polarity information from texts. For textual term representation, different feature selection methods, e.g. term frequency (TF) or term frequency–inverse document frequency (TF–IDF), can yield diverse numbers of text features. In text classification, however, a selected training set may contain noisy documents (...

Suicide is listed in the top ten causes of death in Taiwan. Previous studies have pointed out that psychiatric patients having suicide attempts in their history are more likely to attempt suicide again than non-psychiatric patients. Therefore, how to predict the future multiple suicide attempts of psychiatric patients is an important issue of publi...

Many data mining algorithms cannot handle incomplete datasets where some data samples are missing attribute values. To solve this problem, missing value imputation is usually conducted and commonly based on reasoning from observed data or complete data to provide estimated replacements for missing values. In general, missing imputation methods can...

Background Several prognostic scores have been proposed to predict functional outcomes after an acute ischemic stroke (AIS). Most of these scores are based on structured information and have been used to develop prediction models via the logistic regression method. With the increased use of electronic health records and the progress in computationa...

Class imbalanced medical datasets, such as cancer prediction, contain imbalanced numbers of data in different classes leading to skewed class distribution, which makes it very difficult for a classifier to distinguish between minority (i.e. cancer) and majority (i.e. non-cancer) classes. Related studies in the literature have proposed different typ...

Background Conventional prognostic scores usually require predefined clinical variables to predict outcome. The advancement of natural language processing has made it feasible to derive meaning from unstructured data. We aimed to test whether using unstructured text in electronic health records can improve the prediction of functional outcome after...

Online review helpfulness prediction is an important research issue in electronic commerce and data mining. However, the collected datasets used for the analysis and prediction of the helpfulness of online reviews often contain some missing attribute values, such as reviewer background and rating information. In related literatures, many studies ha...

Bankruptcy prediction and credit scoring are major problems in financial distress prediction. Studies have shown that prediction models can be made more effective by performing data preprocessing procedures. Moreover, classifier ensembles are likely to outperform single classifiers. Although feature selection, instance selection, and classifier ens...

Background Acute stroke is an urgent medical condition that requires immediate assessment and treatment. Prompt identification of patients with suspected stroke at emergency department (ED) triage followed by timely activation of code stroke systems is the key to successful management of stroke. While false negative detection of stroke may prevent...

BACKGROUND Several prognostic scores have been proposed to predict functional outcomes after an acute ischemic stroke (AIS). Most of these scores are based on structured information and have been used to develop prediction models via the logistic regression method. With the increased use of electronic health records and the progress in computationa...

Falls are one of the most common accidents among inpatients and may result in extended hospitalization and increased medical costs. Constructing a highly accurate fall prediction model could effectively reduce the rate of patient falls, further reducing unnecessary medical costs and patient injury. This study applied data mining techniques on a hos...

The considerable volume of online reviews for today's hotels are is difficult for review readers to manually process. Automatic review summarizations are a promising direction for improving information processing of travelers. Studies have focused on extracting relevant text features or performing sentiment analysis to compile review summaries. How...

Readmissions after stroke are not only associated with greater levels of disability and a higher risk of mortality but also increase overall medical costs. Predicting readmission risk and understanding its causes are thus essential for healthcare resource allocation and quality improvement planning. By using machine learning techniques on initial a...

The safety of high-alert medication treatment is still a challenge all over the world. Approximately one-half of adverse drug events (ADEs) are related to high-alert medications, which motivates us to improve the predicament faced in clinical practice. The purpose of this study is to use machine-learning techniques to predict the risk of high-alert...

Opinion mining focuses on extracting polarity information from texts. For textual term representation, different feature selection methods, e.g. term frequency (TF) or term frequency–inverse document frequency (TF–IDF), can yield diverse numbers of text features. In text classification, however, a selected training set may contain noisy documents (...

Background Atrial fibrillation (AF) is the most common cardiac rhythm disorder associated with stroke. Increased risk of stroke is the same regardless of whether the AF is permanent or paroxysmal. However, detecting paroxysmal AF is challenging and resource intensive. We aimed to develop a predictive model for AF in patients with acute ischemic str...

The incidence rate of pressure injury is a critical nursing quality indicator in clinic care; consequently, factors causing pressure injury are diverse and complex. The early prevention of pressure injury and monitoring of these complex high-risk factors are critical to reduce the patients' pain, prevent further surgical treatment, avoid prolonged...

Ischemic stroke is a major cause of death and disability in adulthood worldwide. Because it has highly heterogeneous phenotypes, phenotyping of ischemic stroke is an essential task for medical research and clinical prognostication. However, this task is not a trivial one when the study population is large. Phenotyping of ischemic stroke depends pri...

BACKGROUND Taiwan’s National Health Insurance (NHI) claims database has been widely used for clinical and health services research. However, its use, and perhaps misuse, has incurred criticism and even litigation. OBJECTIVE This study updates the bibliometric profile of the literature using NHI claims data. METHODS PubMed was used to locate publi...

Background: Studies using Taiwan's National Health Insurance (NHI) claims data have expanded rapidly both in quantity and quality during the first decade following the first study published in 2000. However, some of these studies were criticized for being merely data-dredging studies rather than hypothesis-driven. In addition, the use of claims da...

The number of received citations have been used as an indicator of the impact of academic publications. Developing tools to find papers that have the potential to become highly-cited has recently attracted increasing scientific attention. Topics of concern by scholars may change over time in accordance with research trends, resulting in changes in...

Background: Reducing hospital readmissions for stroke remains a significant challenge to improve outcomes and decrease healthcare costs. Methods: We analyzed 10,034 adult patients with ischaemic stroke who presented within 24 hours of onset from a hospital-based stroke registry. The risk factors for early return to hospital after discharge were...

Background and Purpose Recurrent ischemic strokes increase the risk of disability and mortality. The role of conventional risk factors in recurrent strokes may change due to increased awareness of prevention strategies. The aim of this study was to explore the potential risk factors besides conventional ones which may help to affect the advance in...

BACKGROUND Unipolar major depressive disorder (MDD) and bipolar disorder are two major mood disorders. The two disorders have different treatment strategies and prognoses. However, bipolar disorder may begin with depression and could be diagnosed as MDD at the initial stage which may contribute to treatment failure. Previous studies indicated that...

Background: Unipolar major depressive disorder (MDD) and bipolar disorder are two major mood disorders. The two disorders have different treatment strategies and prognoses. However, bipolar disorder may begin with depression and could be diagnosed as MDD in the initial stage, which may later contribute to treatment failure. Previous studies indica...

Purpose The purpose of this paper is to combine basic movie information factors, external factors and review factors, to predict box-office performance and identify the most crucial factor of influence for box-office performance. Design/methodology/approach Five movie genres and first-week movie reviews found on IMDb were collected. The movie re...

Class-imbalanced datasets, i.e., those with the number of data samples in one class being much larger than that in another class, occur in many real-world problems. Using these datasets, it is very difficult to construct effective classifiers based on the current classification algorithms, especially for distinguishing small or minority classes fro...

Blood transfusion is a common and often necessary medical procedure during surgery. However, most physicians rely on their personal clinical experience to determine whether a patient requires a transfusion. This generally involves considering the risk of blood loss during surgery, and the preparation of blood is thus regularly requested before surg...

Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug interactions (DDIs). Approximately 50% of digoxin toxicity cases are preventable, which motivated us to improve the treatment outcomes of digoxin. The objective of this study is to apply machine learning techniques to predict the appropriateness of init...

Prosthodontic treatment has been a crucial part of dental treatment for patients with full mouth rehabilitation. Dental implant surgeries that replace conventional dentures using titanium fixtures have become the top choice. However, because of the wide-ranging scope of implant surgeries, patients’ body conditions, surgeons’ experience, and the cho...

Objective: To reduce errors in determining eligibility for intravenous thrombolytic therapy (IVT) in stroke patients through use of an enhanced task-specific electronic medical record (EMR) interface powered by natural language processing (NLP) techniques. Materials and methods: The information processing algorithm utilized MetaMap to extract me...

With the rapid development of Web 2.0, travelers have started sharing their travel experiences on websites. The expanding amount of online hotel reviews results in the problem of information overload. Therefore, the effective identification of helpful reviews has become an important research issue. In this study, online hotel reviews were collected...

Extracting the bag-of-words (BoW) feature from images has been widely used for image classification. In general, some local keypoints are first of all detected from each image and the keypoint descriptor, such as scale-invariant feature transform (SIFT), is extracted. Then, the keypoint descriptors of a given image dataset are tokenized (or cluster...

Class imbalance is often a problem in various real-world data sets, where one class (i.e. the minority class) contains a small number of data points and the other (i.e. the majority class) contains a large number of data points. It is notably difficult to develop an effective model using current data mining and machine learning algorithms without c...

Chronic kidney disease (CKD) has attracted considerable attention in the public health domain in recent years. Researchers have exerted considerable effort in attempting to identify critical factors that may affect the deterioration of CKD. In clinical practice, the physical conditions of CKD patients are regularly recorded. The data of CKD patient...

Online travel forums and social networks have become the most popular platform for sharing travel information, with enormous numbers of reviews posted daily. Automatically generated hotel summaries could aid travelers in selecting hotels. This study proposes a novel multi-text summarization technique for identifying the top-k most informative sente...

Background and objective: Return visits (RVs) to the emergency department (ED) consume medical resources and may represent a patient safety issue. The occurrence of unexpected RVs is considered a performance indicator for ED care quality. Because children are susceptible to medical errors and utilize considerable ED resources, knowing the factors...

Purpose Most academic libraries provide book recommendation services to enable readers to recommend books to the libraries. To facilitate decision-making in book acquisition, this study aimed to develop a method to determine the ranking of the recommended books based on the recommender network. Design/methodology/approach The recommender network...

Introduction: Readmissions after stroke are costly. Risk assessment using information available upon admission could identify high-risk patients for potential interventions to reduce readmissions. Baseline stroke severity has been suspected to be a factor in readmission: however, the exact nature of the impact has not been adequately understood. Me...

Background Borderline personality disorder (BPD) is a complex clinical state with highly polymorphic symptoms and signs. Studies have demonstrated that people with a BPD diagnosis are likely to have numerous co-occurring psychiatric disorders and physical comorbidities. The aim of our study was to obtain further insight about the associations among...

Classification and numeric estimation are the two most common types of data mining. The goal of classification is to predict the discrete type of output values whereas estimation is aimed at finding the continuous type of output values. Predictive data mining is generally achieved by using only one specific statistical or machine learning technique...

Classification is one of the most important technologies used in data mining. Researchers have recently proposed several classification techniques based on the concept of association rules (also known as CBA-based methods). Experimental evaluations on these studies show that in average the CBA-based approaches can yield higher accuracy than some of...

In the diagnosis of late-onset hypogonadism (LOH), the Androgen Deficiency in the Aging Male (ADAM) questionnaire or Aging Males' Symptoms (AMS) scale can be used to assess related symptoms. Subsequently, blood tests are used to measure serum testosterone levels. However, results obtained using ADAM and AMS have revealed no significant correlations...

The tourism industry has been strongly influenced by electronic word-of-mouth (eWOM) in recent years. Currently, there are only limited studies available that look into hotel review helpfulness. This present study addresses three hidden assumptions prevalent in online review studies: (1) all reviews are visible equally to online users, (2) review r...

Product reviews have gained much popularity in recent years. This study examines the theoretical foundation of review helpfulness and reports how the interactions among three user-controllable filters together with three groups of predictors affect review helpfulness. Reviews from TripAdvisor.com were analyzed against three analytical models. The r...

Introduction: Readmissions after stroke are costly. Risk assessment using information available upon admission could identify high-risk patients for potential interventions to reduce readmissions. Baseline stroke severity has been suspected to be a factor in readmission; however, the exact nature of the impact has not been adequately understood....

Background Stroke severity is an important outcome predictor for intracerebral hemorrhage (ICH) but is typically unavailable in administrative claims data. We validated a claims-based stroke severity index (SSI) in patients with ICH in Taiwan. Methods Consecutive ICH patients from hospital-based stroke registries were linked with a nationwide clai...

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.je.2016.08.003.

Background Ascertaining stroke severity in claims data-based studies is difficult because clinical information is unavailable. We assessed the predictive validity of a claims-based stroke severity index (SSI) and determined whether it improves case-mix adjustment. Methods We analyzed patients with acute ischemic stroke (AIS) from hospital-based str...

Aim: To develop a risk stratification model for the early diagnosis of borderline personality disorder (BPD) using Taiwan National Health Insurance Research Database. Methods: We conducted a retrospective case-control study of 6132 patients (292 BPD patients and 5840 control subjects) who were selected from the National Health Insurance Research...

Purpose – The purpose of this paper is to focus on examining the research impact of papers written with and without funding. Specifically, the citation analysis method is used to compare the general and funded papers published in two leading international conferences, which are ACM SIGIR and ACM SIGKDD. Design/methodology/approach – The authors in...

The success of object categorization is heavily dependent on the extracted image descriptors. In general, image or region segmentation is usually performed to segment an image into several regions or objects, and then some level-level features, such as color and texture, are extracted from each region. As a result, the region descriptor or the comb...

Determining the likelihood of a prolonged length of stay (LOS) for surgery patients can improve medical resource management. This study was aimed at developing predictive models for determining whether patient LOS is within the standard LOS after surgery. This study analyzed the complete historical medical records and lab data of 896 clinical cases...

Purpose: Confounding by disease severity has been viewed as an intractable problem in claims-based studies. A novel 7-variable stroke severity index (SSI) was designed for estimating stroke severity by using claims data. This study compared the performance of mortality models with various proxy measures of stroke severity, including the SSI, in pa...

Background: To collect medical datasets, it is usually the case that a number of data samples contain some missing values. Performing the data mining task over the incomplete datasets is a difficult problem. In general, missing value imputation can be approached, which aims at providing estimations for missing values by reasoning from the observed...

Background: Understanding the factors that influence the hospital length of stay (LOS) for patients with stroke will help in discharge planning and stroke unit management. We explored how intravenous thrombolysis (IVT) affects LOS in an acute-care hospital setting. Methods: We analyzed adult patients with ischemic stroke who presented within 48...

A return visit (RV) to the emergency department (ED) is usually used as a quality indicator for EDs. A thorough comprehension of factors affecting RVs is beneficial to enhancing the quality of emergency care. We performed this study to identify pediatric patients at high risk of RVs using readily available characteristics during an ED visit. We ret...

Periodic patterns and cyclic patterns have been used to discover recurring patterns in sequence databases. Toroslu (2003) proposed cyclically repeated pattern (CRP) mining, in which a new parameter called repetition support is considered in the mining process. In a data sequence, the occurrence of a subsequence must satisfy a single user-specified...

The size of medical datasets is usually very large, which directly affects the computational cost of the data mining process. Instance selection is a data preprocessing step in the knowledge discovery process, which can be employed to reduce storage requirements while also maintaining the mining quality. This process aims to filter out outliers (or...

The purpose of this study was to explore the factors influencing the turnover intention of dentists in hospitals in Taiwan.Materials and methodsNationwide, 175 structured questionnaires were returned from dentists who were working for a hospital of the Bureau of the National Health Insurance, Taipei division, representing a 37% response rate.Result...

This study uncovers the effect of the length, recency, frequency, monetary, and profit (LRFMP) customer value model in a logistics company to predict customer churn. This unique context has useful business implications compared to the main stream customer churn studies where individual customers (rather than business customers) are the main focus....

Purpose – Conference publications are an important aspect of research activities. There are generally both oral presentations and poster sessions at large international conferences. One can hypothesise that, for the same conferences, the papers presented in oral sessions should have a higher research impact than the papers presented in poster sessi...

Purpose – Credit ratings have become one of the primary references for financial institutions to assess credit risk. Conventional credit rating approaches mainly concentrated on two-class classification (i.e. good or bad credit), which lacks adequate precision to perform credit risk evaluations in practice. In addition, most of previous researches...

An early warning system can help to identify at-risk students, or predict student learning performance by analyzing learning portfolios recorded in a learning management system (LMS). Although previous studies have shown the applicability of determining learner behaviors from an LMS, most investigated datasets are not assembled from online learning...

Purpose – Ranking relevant journals is very critical for researchers to choose their publication outlets, which can affect their research performance. In the management information systems (MIS) subject, many related studies conducted surveys as the subjective method for identifying MIS journal rankings. However, very few consider other objective m...

Pseudorelevance feedback (PRF) was proposed to solve the limitation of relevance feedback (RF), which is based on the user-in-the-loop process. In PRF, the top-k retrieved images are regarded as PRF. Although the PRF set contains noise, PRF has proven effective for automatically improving the overall retrieval result. To implement PRF, the Rocchio...

Objectives: Due to the narrow therapeutic range and high drug-to-drug interactions (DDIs), improving the adequate use of warfarin for the elderly is crucial in clinical practice. This study examines whether the effectiveness of using warfarin among elderly inpatients can be improved when machine learning techniques and data from the laboratory inf...

Companies can use customer segmentation to group customers with similar characteristics together and identify the differences between groups to develop marketing strategies. This study investigates the problem of customer segmentation in relation to automotive customer relationship management and presents a real case study of an automobile dealer i...

Access control is a prime technology to prevent unauthorized access to private information, which is one of the essential issues appearing in secure group communication (SGC) of wireless sensor networks (WSNs). Many studies have made good progress on access control; however, their methods are inadequate to cope with this new issue for SGC-based WSN...

Sequential pattern mining (SPM) is an important technique for determining time-related behavior in sequence databases. In real-life applications, the frequencies for various items in a sequence database are not exactly equal. If all items are set with the same minimum support, the rare item problem may result, meaning that we are unable to effectiv...

Purpose – Customer lifetime value (CLV) has received increasing attention in database marketing. Enterprises can retain valuable customers by the correct prediction of valuable customers. In the literature, many data mining and machine learning techniques have been applied to develop CLV models. Specifically, hybrid techniques have shown their supe...

In today's business environment, there is tremendous interest in the mining of interesting patterns for superior decision making. Although many successful customer relationship management (CRM) applications have been developed based on sequential pattern mining techniques, they basically assume that the importance of each customer is the same. Prev...

For financial institutions, the ability to predict or forecast business failures is crucial, as incorrect decisions can have direct financial consequences. Bankruptcy prediction and credit scoring are the two major research problems in the accounting and finance domain. In the literature, a number of models have been developed to predict whether bo...

Safety of anticoagulant administration has been a primary concern of the Joint Commission on Accreditation of Healthcare Organizations. Among all anticoagulants, warfarin has long been listed among the top ten drugs causing adverse drug events. Due to narrow therapeutic range and significant side effects, warfarin dosage determination becomes a cha...

Due to the explosion of knowledge in the library, the librarians need to make effective decisions in book acquisition under the limited budget. Since librarians can not fully realize the needs of readers, many libraries provide the book recommendation service such that the readers can recommend the books to the libraries. However, the readers may o...

In business applications, there have been tremendous interests in analysing customers' repeated purchase behaviour. Recently, the concepts of periodic pattern and cyclic pattern are used to discover recurring patterns from customer sequence database. Toroslu (2003) proposed cyclic pattern mining, which considers a new parameter, named repetition su...

For superior decision making, the mining of interesting patterns and rules becomes one of the most indispensible tasks in today's business environment. Although there have been many successful customer relationship management (CRM) applications based on sequential pattern mining techniques, they basically assume that the importance of each customer...