AIMC Topic: Republic of Korea
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Care robot research and development plan for disability and aged care in Korea: A mixed-methods user participation study.
Assistive technology : the official journal of RESNA
Feb 24, 2022
The population of Korea is aging rapidly, and this has led to a care burden for caregivers. Without adequate caregivers to address the increased burden, people with significant disabilities and older adults with disabilities who have greatly reduced ...
Machine learning-based prediction of critical illness in children visiting the emergency department.
PloS one
Feb 17, 2022
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...
Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.
Scientific reports
Feb 10, 2022
The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult for physicians to screen thousands of people, high-accuracy and interpretable methods need to be prese...
Asymmetry between right and left fundus images identified using convolutional neural networks.
Scientific reports
Jan 27, 2022
We analyzed fundus images to identify whether convolutional neural networks (CNNs) can discriminate between right and left fundus images. We gathered 98,038 fundus photographs from the Gyeongsang National University Changwon Hospital, South Korea, an...
Temporal Prediction of Paralytic Shellfish Toxins in the Mussel Using a LSTM Neural Network Model from Environmental Data.
Toxins
Jan 12, 2022
Paralytic shellfish toxins (PSTs) are produced mainly by (formerly ). Since 2000, the National Institute of Fisheries Science (NIFS) has been providing information on PST outbreaks in Korean coastal waters at one- or two-week intervals. However, a d...
Artificial intelligence predicts clinically relevant atrial high-rate episodes in patients with cardiac implantable electronic devices.
Scientific reports
Jan 7, 2022
To assess the utility of machine learning (ML) algorithms in predicting clinically relevant atrial high-rate episodes (AHREs), which can be recorded by a pacemaker. We aimed to develop ML-based models to predict clinically relevant AHREs based on the...
Predicting speech discrimination scores from pure-tone thresholds-A machine learning-based approach using data from 12,697 subjects.
PloS one
Dec 31, 2021
Diagnostic tests for hearing impairment not only determines the presence (or absence) of hearing loss, but also evaluates its degree and type, and provides physicians with essential data for future treatment and rehabilitation. Therefore, accurately ...
Infant
Speech Reception Threshold Test
Algorithms
Adolescent
Republic of Korea
Reproducibility of Results
Hearing Loss
Computational Biology
Child, Preschool
Female
Humans
Aged
Models, Statistical
Speech Perception
Infant, Newborn
Child
Aged, 80 and over
Neural Networks, Computer
Audiometry, Pure-Tone
Auditory Threshold
Adult
Young Adult
Machine Learning
Hearing
Discrimination Learning
Male
Middle Aged
Measuring Patient Similarity on Multiple Diseases by Joint Learning via a Convolutional Neural Network.
Sensors (Basel, Switzerland)
Dec 25, 2021
Patient similarity research is one of the most fundamental tasks in healthcare, helping to make decisions without incurring additional time and costs in clinical practices. Patient similarity can also apply to various medical fields, such as cohort a...
Deep learning computer-aided detection system for pneumonia in febrile neutropenia patients: a diagnostic cohort study.
BMC pulmonary medicine
Dec 7, 2021
BACKGROUND: Diagnosis of pneumonia is critical in managing patients with febrile neutropenia (FN), however, chest X-ray (CXR) has limited performance in the detection of pneumonia. We aimed to evaluate the performance of a deep learning-based compute...
Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models.
Computational intelligence and neuroscience
Nov 27, 2021
Nowadays, ocean observation technology continues to progress, resulting in a huge increase in marine data volume and dimensionality. This volume of data provides a golden opportunity to train predictive models, as the more the data is, the better the...
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