Bohyun Wang
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View article: Development of an innovative approach using portable eye tracking to assist ADHD screening: a machine learning study
Development of an innovative approach using portable eye tracking to assist ADHD screening: a machine learning study Open
Introduction Attention-deficit/hyperactivity disorder (ADHD) affects a significant proportion of the pediatric population, making early detection crucial for effective intervention. Eye movements are controlled by brain regions associated …
View article: A Novel Methodology for Forecasting Business Cycles Using ARIMA and Neural Network with Weighted Fuzzy Membership Functions
A Novel Methodology for Forecasting Business Cycles Using ARIMA and Neural Network with Weighted Fuzzy Membership Functions Open
Economic forecasting is crucial since it benefits many different parties, such as governments, businesses, investors, and the general public. This paper presents a novel methodology for forecasting business cycles using an autoregressive i…
View article: Classification Model of Clock Drawing Test Based on Contrastive Learning Using Multi-Channel Features With Channel-Spatial Attention
Classification Model of Clock Drawing Test Based on Contrastive Learning Using Multi-Channel Features With Channel-Spatial Attention Open
The Clock Drawing Test (CDT) is a professional examination that can detect cognitive impairments, such as Parkinson’s and Alzheimer’s diseases, based on scoring criteria. The pooling layers of a convolutional neural network (CNN) compress …
View article: Prediction of Diagnosis and Treatment Response in Adolescents With Depression by Using a Smartphone App and Deep Learning Approaches: Usability Study
Prediction of Diagnosis and Treatment Response in Adolescents With Depression by Using a Smartphone App and Deep Learning Approaches: Usability Study Open
Background Lack of quantifiable biomarkers is a major obstacle in diagnosing and treating depression. In adolescents, increasing suicidality during antidepressant treatment further complicates the problem. Objective We sought to evaluate d…
View article: Prediction of Diagnosis and Treatment Response in Adolescents With Depression by Using a Smartphone App and Deep Learning Approaches: Usability Study (Preprint)
Prediction of Diagnosis and Treatment Response in Adolescents With Depression by Using a Smartphone App and Deep Learning Approaches: Usability Study (Preprint) Open
BACKGROUND Lack of quantifiable biomarkers is a major obstacle in diagnosing and treating depression. In adolescents, increasing suicidality during antidepressant treatment further complicates the problem. OBJECTIVE We sought to evaluat…
View article: Feature Selection Method Using Multi-Agent Reinforcement Learning Based on Guide Agents
Feature Selection Method Using Multi-Agent Reinforcement Learning Based on Guide Agents Open
In this study, we propose a method to automatically find features from a dataset that are effective for classification or prediction, using a new method called multi-agent reinforcement learning and a guide agent. Each feature of the datas…
View article: Zoom-In Neural Network Deep-Learning Model for Alzheimer’s Disease Assessments
Zoom-In Neural Network Deep-Learning Model for Alzheimer’s Disease Assessments Open
Deep neural networks have been successfully applied to generate predictive patterns from medical and diagnostic data. This paper presents an approach for assessing persons with Alzheimer’s disease (AD) mild cognitive impairment (MCI), comp…
View article: Feature selection method using multi-agent reinforcement learning based on guide agents
Feature selection method using multi-agent reinforcement learning based on guide agents Open
In this study, we propose a method to automatically find features from a dataset that are effective for classification or prediction, using a new method called multi-agent reinforcement learning and a guide agent. Each feature of the datas…
View article: A Study on the Features Selection Algorithm Based on the Measurement Method of the Distance Between Normal Distributions for Classification in Machine Learning
A Study on the Features Selection Algorithm Based on the Measurement Method of the Distance Between Normal Distributions for Classification in Machine Learning Open
Feature selection is an important technique that simplifies machine learning models to easily understand, shorten learning time, and reduce curve over-fitting or under-fitting. This paper presents a shape selection algorithm based on a met…
View article: Prediction of diagnosis and treatment response in adolescents with depression using smartphone application and machine learning approaches: a pilot study (Preprint)
Prediction of diagnosis and treatment response in adolescents with depression using smartphone application and machine learning approaches: a pilot study (Preprint) Open
BACKGROUND Lack of quantifiable biomarkers is a major obstacle in making diagnosis and predicting treatment response in depression. In adolescents, increasing suicidality during antidepressant treatment further complicate the problems. Em…