Chun‐Hung Richard Lin
YOU?
Author Swipe
View article: Tide modulated ocean to Earth energy conversion quantified with coastal fiber sensing
Tide modulated ocean to Earth energy conversion quantified with coastal fiber sensing Open
View article: FADEL: Ensemble Learning Enhanced by Feature Augmentation and Discretization
FADEL: Ensemble Learning Enhanced by Feature Augmentation and Discretization Open
In recent years, data augmentation techniques have become the predominant approach for addressing highly imbalanced classification problems in machine learning. Algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) and …
View article: A Multi-Stage Framework for Kawasaki Disease Prediction Using Clustering-Based Undersampling and Synthetic Data Augmentation: Cross-Institutional Validation with Dual-Center Clinical Data in Taiwan
A Multi-Stage Framework for Kawasaki Disease Prediction Using Clustering-Based Undersampling and Synthetic Data Augmentation: Cross-Institutional Validation with Dual-Center Clinical Data in Taiwan Open
Kawasaki disease (KD) is a rare yet potentially life-threatening pediatric vasculitis that, if left undiagnosed or untreated, can result in serious cardiovascular complications. Its heterogeneous clinical presentation poses diagnostic chal…
View article: Predicting Fetal Growth with Curve Fitting and Machine Learning
Predicting Fetal Growth with Curve Fitting and Machine Learning Open
Monitoring fetal growth throughout pregnancy is essential for early detection of developmental abnormalities. This study developed a Taiwan-specific fetal growth reference using a web-based data collection platform and polynomial regressio…
View article: Factors Influencing Consumer Buying Behavior for Smart Home Technologies
Factors Influencing Consumer Buying Behavior for Smart Home Technologies Open
Smart home technologies offer numerous benefits to consumers. This study explored the relationship between the perceived benefits of and likelihood of adopting smart home technologies among Taiwanese consumers. The study conducted a survey…
View article: Enhancing generalization in a Kawasaki Disease prediction model using data augmentation: Cross-validation of patients from two major hospitals in Taiwan
Enhancing generalization in a Kawasaki Disease prediction model using data augmentation: Cross-validation of patients from two major hospitals in Taiwan Open
Kawasaki Disease (KD) is a rare febrile illness affecting infants and young children, potentially leading to coronary artery complications and, in severe cases, mortality if untreated. However, KD is frequently misdiagnosed as a common fev…
View article: Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours
Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours Open
The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model's decision-making…
View article: Serum Potassium Monitoring using AI-enabled Smart Watch Electrocardiograms
Serum Potassium Monitoring using AI-enabled Smart Watch Electrocardiograms Open
Background Hyperkalemia poses a significant risk of sudden cardiac death, especially for those with end-stage renal diseases (ESRD). Smartwatches with ECG capabilities offer a promising solution for continuous, non-invasive monitoring usin…
View article: Joint beamforming and power splitting design for MISO downlink communication with SWIPT: a comparison between cell-free massive MIMO and small-cell deployments
Joint beamforming and power splitting design for MISO downlink communication with SWIPT: a comparison between cell-free massive MIMO and small-cell deployments Open
Simultaneous wireless information and power transfer (SWIPT) has been advocated as a highly promising technology for enhancing the capabilities of 5G and 6G devices. However, the challenge of dealing with large propagation path loss poses …
View article: Utilizing Nearest-Neighbor Clustering for Addressing Imbalanced Datasets in Bioengineering
Utilizing Nearest-Neighbor Clustering for Addressing Imbalanced Datasets in Bioengineering Open
Imbalance classification is common in scenarios like fault diagnosis, intrusion detection, and medical diagnosis, where obtaining abnormal data is difficult. This article addresses a one-class problem, implementing and refining the One-Cla…
View article: Secure Collaborative Computing for Linear Regression
Secure Collaborative Computing for Linear Regression Open
Machine learning usually requires a large amount of training data to build useful models. We exploit the mathematical structure of linear regression to develop a secure and privacy-preserving method that allows multiple parties to collabor…
View article: Development and validation of a deep learning pipeline to measure pericardial effusion in echocardiography
Development and validation of a deep learning pipeline to measure pericardial effusion in echocardiography Open
Objectives The aim of this study was to develop a deep-learning pipeline for the measurement of pericardial effusion (PE) based on raw echocardiography clips, as current methods for PE measurement can be operator-dependent and present chal…
View article: Monascin and ankaflavin prevents metabolic disorder by blood glucose regulatory, hypolipidemic, and anti-inflammatory effects in high fructose and high fat diet-induced hyperglycemic rat
Monascin and ankaflavin prevents metabolic disorder by blood glucose regulatory, hypolipidemic, and anti-inflammatory effects in high fructose and high fat diet-induced hyperglycemic rat Open
Monascin (MS) and ankaflavin (AK) produced by Monascus purpureus fermented red mold dioscorea (RMD) elicit an anti-diabetes effect in streptozocin-induced type 1 diabetes. However, their effects on preventing metabolic disorder with type 2…
View article: Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus
Using Machine Learning for the Risk Factors Classification of Glycemic Control in Type 2 Diabetes Mellitus Open
Several risk factors are related to glycemic control in patients with type 2 diabetes mellitus (T2DM), including demographics, medical conditions, negative emotions, lipid profiles, and heart rate variability (HRV; to present cardiac auton…
View article: Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks
Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks Open
The advent of simultaneous wireless information and power (SWIPT) has been regarded as a promising technique to provide power supplies for an energy sustainable Internet of Things (IoT), which is of paramount importance due to the prolifer…
View article: Use of Machine Learning to Differentiate Children With Kawasaki Disease From Other Febrile Children in a Pediatric Emergency Department
Use of Machine Learning to Differentiate Children With Kawasaki Disease From Other Febrile Children in a Pediatric Emergency Department Open
Importance Early awareness of Kawasaki disease (KD) helps physicians administer appropriate therapy to prevent acquired heart disease in children. However, diagnosing KD is challenging and relies largely on subjective diagnosis criteria. O…
View article: Use of a Deep-Learning Algorithm to Guide Novices in Performing Focused Assessment With Sonography in Trauma
Use of a Deep-Learning Algorithm to Guide Novices in Performing Focused Assessment With Sonography in Trauma Open
This quality improvement study compares the diagnostic quality and completion time between ultrasonography operators guided by artificial intelligence vs those without such assistance.
View article: VOC Emissions from a Rendering Plant and Evaluation for Removal of Pentanal by Oxidization Using Hydrogen Peroxide
VOC Emissions from a Rendering Plant and Evaluation for Removal of Pentanal by Oxidization Using Hydrogen Peroxide Open
Rendering plants treat dead livestock and produce grease and bone meal. In a rendering plant, the cooking and drying processes are the main sources of odor emissions. Non-fresh dead livestock reduce the performance of odor control devices,…
View article: Utilization of Personalized Machine-Learning to Screen for Dysglycemia from Ambulatory ECG, toward Noninvasive Blood Glucose Monitoring
Utilization of Personalized Machine-Learning to Screen for Dysglycemia from Ambulatory ECG, toward Noninvasive Blood Glucose Monitoring Open
Blood glucose (BG) monitoring is important for critically ill patients, as poor sugar control has been associated with increased mortality in hospitalized patients. However, constant BG monitoring can be resource-intensive and pose a healt…
View article: Using Deep Transfer Learning to Detect Hyperkalemia From Ambulatory Electrocardiogram Monitors in Intensive Care Units: Personalized Medicine Approach
Using Deep Transfer Learning to Detect Hyperkalemia From Ambulatory Electrocardiogram Monitors in Intensive Care Units: Personalized Medicine Approach Open
Background Hyperkalemia is a critical condition, especially in intensive care units. So far, there have been no accurate and noninvasive methods for recognizing hyperkalemia events on ambulatory electrocardiogram monitors. Objective This s…
View article: Machine learning models for predicting in-hospital mortality in patient with sepsis: Analysis of vital sign dynamics
Machine learning models for predicting in-hospital mortality in patient with sepsis: Analysis of vital sign dynamics Open
Purpose To build machine learning models for predicting the risk of in-hospital death in patients with sepsis within 48 h, using only dynamic changes in the patient's vital signs. Methods This retrospective observational cohort study enrol…
View article: Development and validation of an end-to-end deep learning pipeline to measure pericardial effusion in echocardiography
Development and validation of an end-to-end deep learning pipeline to measure pericardial effusion in echocardiography Open
Introduction Cardiac tamponade, caused by pericardial effusion (PE), is a life-threatening condition that can be resolved by timely pericardiocentesis. Nevertheless, PE measurement remains operator-dependent and may be difficult in some ci…
View article: One-Class Machine-Learning Model to Screen for Dysglycemia Using Single Lead ECG in ICU, toward Noninvasive Blood Glucose Monitoring
One-Class Machine-Learning Model to Screen for Dysglycemia Using Single Lead ECG in ICU, toward Noninvasive Blood Glucose Monitoring Open
Blood glucose (BG) monitoring is an important issue for critically ill patients. Previous studies reported that poor sugar control was associated with increased mortality in admitted patients. However, repeated blood glucose monitoring can…
View article: Using Deep Transfer Learning to Detect Hyperkalemia from Ambulatory Electrocardiogram Monitors in Intensive Care Units: A Personalized Medicine approach (Preprint)
Using Deep Transfer Learning to Detect Hyperkalemia from Ambulatory Electrocardiogram Monitors in Intensive Care Units: A Personalized Medicine approach (Preprint) Open
BACKGROUND Hyperkalemia is a critical condition especially in the intensive care unit. There was no accurate and noninvasive method for recognizing hyperkalemia event from ambulatory electrocardiogram monitor so far. OBJECTIVE This stud…
View article: Impact of the synergistic effect of pneumonia and air pollutants on newly diagnosed pulmonary tuberculosis in southern Taiwan
Impact of the synergistic effect of pneumonia and air pollutants on newly diagnosed pulmonary tuberculosis in southern Taiwan Open
A strong association was found between past episodes of PN and the future risk of PTB. In addition, air pollutants including PM2.5, SO2, O3 and NO, together with previous episodes of PN, had both long-term …
View article: Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory
Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory Open
Future wireless networks promise immense increases on data rate and energy efficiency while overcoming the difficulties of charging the wireless stations or devices in the Internet of Things (IoT) with the capability of simultaneous wirele…
View article: Explainable Deep Learning Model to Predict Invasive Bacterial Infection in Febrile Young Infants: A Retrospective Study
Explainable Deep Learning Model to Predict Invasive Bacterial Infection in Febrile Young Infants: A Retrospective Study Open
View article: Remodeling the STEM Curriculum for Future Engineers
Remodeling the STEM Curriculum for Future Engineers Open
Higher education is facing low enrollment, and fewer students are motivated to select STEM majors. This paper reports the results from one university that recently experimentally reformed its undergraduate curriculum to a “theme-based curr…
View article: Deep Learning Assisted Detection of Abdominal Free Fluid in Morison's Pouch During Focused Assessment With Sonography in Trauma
Deep Learning Assisted Detection of Abdominal Free Fluid in Morison's Pouch During Focused Assessment With Sonography in Trauma Open
Background: The use of focused assessment with sonography in trauma (FAST) enables clinicians to rapidly screen for injury at the bedsides of patients. Pre-hospital FAST improves diagnostic accuracy and streamlines patient care, leading to…
View article: Risk of motor vehicle collisions after methadone use
Risk of motor vehicle collisions after methadone use Open
Methadone maintenance treatment (MMT) can alleviate opioid dependence. However, MMT possibly increases the risk of motor vehicle collisions. The current study investigated preliminary estimation of motor vehicle collision incidence rates. …