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Republic of Korea

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Association of time to colonoscopy after a positive fecal test result and fecal hemoglobin concentration with risk of advanced colorectal neoplasia.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: We evaluated the risk of advanced colorectal neoplasia (ACRN) and colorectal cancer (CRC) according to time to colonoscopy after positive fecal immunochemical test (FIT), fecal hemoglobin concentration, and combination of both.

Sequential prediction of quantitative health risk assessment for the fine particulate matter in an underground facility using deep recurrent neural networks.

Ecotoxicology and environmental safety
Particulate matter with aerodynamic diameter less than 2.5 µm (PM) in indoor public spaces such as subway stations, has represented a major public health concern; however, forecasting future sequences of quantitative health risk is an effective metho...

A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Oncotype DX(ODX) is a 21-gene breast cancer recurrence score(RS) assay that aids in decision-making for chemotherapy in early-stage hormone receptor-positive(HR+)breast cancer. We developed a prediction tool using machine learning for hig...

Validation of deep-learning-based triage and acuity score using a large national dataset.

PloS one
AIM: Triage is important in identifying high-risk patients amongst many less urgent patients as emergency department (ED) overcrowding has become a national crisis recently. This study aims to validate that a Deep-learning-based Triage and Acuity Sco...

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BMC geriatrics
BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a ne...

Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images.

IEEE transactions on medical imaging
We propose a framework for localization and classification of masses in breast ultrasound images. We have experimentally found that training convolutional neural network-based mass detectors with large, weakly annotated datasets presents a non-trivia...

Algal Bloom Prediction Using Extreme Learning Machine Models at Artificial Weirs in the Nakdong River, Korea.

International journal of environmental research and public health
In this study, we design an intelligent model to predict chlorophyll-a concentration, which is the primary indicator of algal blooms, using extreme learning machine (ELM) models. Modeling algal blooms is important for environmental management and eco...

A Novel Fundus Image Reading Tool for Efficient Generation of a Multi-dimensional Categorical Image Database for Machine Learning Algorithm Training.

Journal of Korean medical science
BACKGROUND: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system.

Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts.

Computers in biology and medicine
BACKGROUND: This study demonstrates clinical named entity recognition (NER) methods on the clinical texts of rheumatism patients in South Korea. Despite the recent increase in the adoption rate of the electronic health record (EHR) system in global h...