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Machine learning-based cluster analysis identifies four unique phenotypes of patients with degenerative cervical myelopathy with distinct clinical profiles and long-term functional and neurological outcomes.
EBioMedicine
Jul 4, 2024
BACKGROUND: Degenerative cervical myelopathy (DCM), the predominant cause of spinal cord dysfunction among adults, exhibits diverse interrelated symptoms and significant heterogeneity in clinical presentation. This study sought to use machine learnin...
Artificial Intelligence in Urology: Application of a Machine Learning Model to Predict the Risk of Urolithiasis in a General Population.
Journal of endourology
Jul 4, 2024
This research presents our application of artificial intelligence (AI) in predicting urolithiasis risk. Previous applications, including AI for stone disease, have focused on stone composition and aiding diagnostic imaging. AI applications centered a...
Multicenter validation study for automated left ventricular ejection fraction assessment using a handheld ultrasound with artificial intelligence.
Scientific reports
Jul 4, 2024
We sought to validate the ability of a novel handheld ultrasound device with an artificial intelligence program (AI-POCUS) that automatically assesses left ventricular ejection fraction (LVEF). AI-POCUS was used to prospectively scan 200 patients in ...
Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient-nurse verbal communications in home healthcare settings?
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Jul 3, 2024
BACKGROUND: Identifying health problems in audio-recorded patient-nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning cla...
Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights.
Research in nursing & health
Jul 3, 2024
The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes during their lifetimes. We aimed to classify community-dwelling adults with a high risk for prediabet...
Predictive modeling for identification of older adults with high utilization of health and social services.
Scandinavian journal of primary health care
Jul 3, 2024
AIM: Machine learning techniques have demonstrated success in predictive modeling across various clinical cases. However, few studies have considered predicting the use of multisectoral health and social services among older adults. This research aim...
Predicting Alzheimer's disease from cognitive footprints in mid and late life: How much can register data and machine learning help?
International journal of medical informatics
Jul 3, 2024
BACKGROUND: Real-world data with decades-long medical records are increasingly available alongside the growing adoption of machine learning in healthcare research. We evaluated the performance of machine learning models in predicting the risk of Alzh...
A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability.
Accident; analysis and prevention
Jul 3, 2024
One of the main objectives in improving the quality of life for individuals with disabilities, especially those experiencing mobility issues such as the elderly, is to enhance their day-to-day mobility. Enabling easy mobility contributes to their ind...
Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.
Diseases of the colon and rectum
Jul 3, 2024
BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional regression models have limited power to identify complex nonlinear relationships among a large set of v...
Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.
European journal of radiology
Jul 3, 2024
OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-...
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