AIMC Topic: Republic of Korea

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Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study.

Journal of Korean medical science
BACKGROUND: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed ...

Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey.

Biosensors
Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. This paper aims to develop a model that predicts the prevalence of cardiovascular disease using health...

Robust Korean License Plate Recognition Based on Deep Neural Networks.

Sensors (Basel, Switzerland)
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
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...

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

PloS one
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
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
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
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...