AIMC Topic: Republic of Korea
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Machine learning prediction of dropping out of outpatients with alcohol use disorders.
PloS one
Aug 2, 2021
BACKGROUND: Alcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probabili...
Deep radiomics-based survival prediction in patients with chronic obstructive pulmonary disease.
Scientific reports
Jul 26, 2021
Heterogeneous clinical manifestations and progression of chronic obstructive pulmonary disease (COPD) affect patient health risk assessment, stratification, and management. Pulmonary function tests are used to diagnose and classify the severity of CO...
Development of a system to support warfarin dose decisions using deep neural networks.
Scientific reports
Jul 20, 2021
The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 1...
Exploring Factors for Predicting Anxiety Disorders of the Elderly Living Alone in South Korea Using Interpretable Machine Learning: A Population-Based Study.
International journal of environmental research and public health
Jul 18, 2021
This epidemiological study aimed to develop an X-AI that could explain groups with a high anxiety disorder risk in old age. To achieve this objective, (1) this study explored the predictors of senile anxiety using base models and meta models. (2) Thi...
Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.
Clinical nutrition (Edinburgh, Scotland)
Jul 15, 2021
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...
Middle Aged
Nutrition Assessment
Abdomen
Sarcopenia
Republic of Korea
Whole Body Imaging
Muscle, Skeletal
Fluorodeoxyglucose F18
Female
Humans
Intra-Abdominal Fat
Positron Emission Tomography Computed Tomography
Aged
Neural Networks, Computer
Subcutaneous Fat
Body Composition
Male
Retrospective Studies
Radiopharmaceuticals
Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm.
Clinical research in cardiology : official journal of the German Cardiac Society
Jul 14, 2021
OBJECTIVE: Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with ...
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
Jul 12, 2021
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
Jul 8, 2021
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)
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...
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