AIMC Topic: Republic of Korea
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Robust Korean License Plate Recognition Based on Deep Neural Networks.
Sensors (Basel, Switzerland)
Jun 16, 2021
With the rapid rise of private vehicles around the world, License Plate Recognition (LPR) plays a vital role in supporting the government to manage vehicles effectively. However, an introduction of new types of license plate (LP) or slight changes in...
Quantitative gait analysis of idiopathic normal pressure hydrocephalus using deep learning algorithms on monocular videos.
Scientific reports
Jun 11, 2021
A vision-based gait analysis method using monocular videos was proposed to estimate temporo-spatial gait parameters by leveraging deep learning algorithms. This study aimed to validate vision-based gait analysis using GAITRite as the reference system...
A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow-up in patients with acute coronary syndrome.
PloS one
Jun 11, 2021
OBJECTIVE: Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine lear...
COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.
PloS one
Jun 7, 2021
Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrained environments, and a computer-aided detection system (CAD) that can identify pneumonia on CXR may help the triage of patients in those environment ...
Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.
International journal of environmental research and public health
May 24, 2021
Few studies have been conducted to classify and predict the influence of nutritional intake on overweight/obesity, dyslipidemia, hypertension and type 2 diabetes mellitus (T2DM) based on deep learning such as deep neural network (DNN). The present st...
Oncologic Outcomes of Intracorporeal Extracorporeal Urinary Diversion After Robot-Assisted Radical Cystectomy: A Multi-Institutional Korean Study.
Journal of endourology
May 20, 2021
We aimed to compare the oncologic outcomes of intracorporeal urinary diversion (ICUD) and extracorporeal urinary diversion (ECUD) following robot-assisted radical cystectomy (RARC) in patients diagnosed with bladder cancer. Medical records of 730 p...
A comparative study of deep learning-based network model and conventional method to assess beach debris standing-stock.
Marine pollution bulletin
May 11, 2021
The conventional survey of marine debris standing-stock has various drawbacks such as high cost and inaccuracy because the total amount of debris in the whole beach is inferred using the results of the manual investigation in selected narrow areas. T...
Machine Learning Approaches to Identify Factors Associated with Women's Vasomotor Symptoms Using General Hospital Data.
Journal of Korean medical science
May 3, 2021
BACKGROUND: To analyze the factors associated with women's vasomotor symptoms (VMS) using machine learning.
An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates.
Journal of environmental management
May 1, 2021
Species distribution models (SDMs), in which species occurrences are related to a suite of environmental variables, have been used as a decision-making tool in ecosystem management. Complex machine learning (ML) algorithms that lack interpretability ...
Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation.
Journal of medical Internet research
Apr 19, 2021
BACKGROUND: The number of deaths from COVID-19 continues to surge worldwide. In particular, if a patient's condition is sufficiently severe to require invasive ventilation, it is more likely to lead to death than to recovery.
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