AI Medical Compendium Topic

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Republic of Korea

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The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

Skeletal radiology
OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray feat...

Prediction of marbling score and carcass traits in Korean Hanwoo beef cattle using machine learning methods and synthetic minority oversampling technique.

Meat science
Pricing of Hanwoo beef in the Korean market is primarily based on meat quality, and particularly on marbling score. The ability to accurately predict marbling score early in the life of an animal is extremely valuable for producers to meet the requir...

Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine.

International journal of environmental research and public health
This study developed a support vector machine (SVM) algorithm-based prediction model with considering influence factors associated with the swallowing quality-of-life as the predictor variables and provided baseline information for enhancing the swa...

Machine learning-based prediction of radiographic progression in patients with axial spondyloarthritis.

Clinical rheumatology
INTRODUCTION: Machine learning is applied to characterize the risk and predict outcomes in multi-dimensional data. The prediction of radiographic progression in axial spondyloarthritis (axSpA) remains limited. Hence, we tested the feasibility of supe...

Atrial fibrillation classification based on convolutional neural networks.

BMC medical informatics and decision making
BACKGROUND: The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990-2010, respectively. In this cont...

Depression Prediction by Using Ecological Momentary Assessment, Actiwatch Data, and Machine Learning: Observational Study on Older Adults Living Alone.

JMIR mHealth and uHealth
BACKGROUND: Although geriatric depression is prevalent, diagnosis using self-reporting instruments has limitations when measuring the depressed mood of older adults in a community setting. Ecological momentary assessment (EMA) by using wearable devic...

Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches.

PloS one
In this research, climate classification maps over the Korean Peninsula at 1 km resolution were generated using the satellite-based climatic variables of monthly temperature and precipitation based on machine learning approaches. Random forest (RF), ...

A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England)
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...