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Deep-learning-based pelvic automatic segmentation in pelvic fractures.
Scientific reports
May 28, 2024
With the recent increase in traffic accidents, pelvic fractures are increasing, second only to skull fractures, in terms of mortality and risk of complications. Research is actively being conducted on the treatment of intra-abdominal bleeding, the pr...
A machine learning analysis of predictors of future hypertension in a young population.
Minerva cardiology and angiology
May 27, 2024
BACKGROUND: Early diagnosis of hypertension (HT) is crucial for preventing end-organ damage. This study aims to identify the risk factors for future HT in young individuals through the application of machine learning (ML) models.
Across Sessions and Subjects Domain Adaptation for Building Robust Myoelectric Interface.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 27, 2024
Gesture interaction via surface electromyography (sEMG) signal is a promising approach for advanced human-computer interaction systems. However, improving the performance of the myoelectric interface is challenging due to the domain shift caused by t...
Enhanced reliability and time efficiency of deep learning-based posterior tibial slope measurement over manual techniques.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
May 26, 2024
PURPOSE: Multifaceted factors contribute to inferior outcomes following anterior cruciate ligament (ACL) reconstruction surgery. A particular focus is placed on the posterior tibial slope (PTS). This study introduces the integration of machine learni...
A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity.
Journal of affective disorders
May 26, 2024
BACKGROUND: Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findi...
Real-time driving risk prediction using a self-attention-based bidirectional long short-term memory network based on multi-source data.
Accident; analysis and prevention
May 25, 2024
Early warning of driving risks can effectively prevent collisions. However, numerous studies that predicted driving risks have suffered from the use of single data sources, insufficiently advanced models, and lack of time window analysis. To address ...
Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.
NeuroImage
May 25, 2024
Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders...
Machine learning identifies factors most associated with seeking medical care for migraine: Results of the OVERCOME (US) study.
Headache
May 24, 2024
OBJECTIVE: Utilize machine learning models to identify factors associated with seeking medical care for migraine.
Effects of midwifery and nursing students' readiness about medical Artificial intelligence on Artificial intelligence anxiety.
Nurse education in practice
May 24, 2024
BACKGROUND: Artificial intelligence technologies are one of the most important technologies of today. Developments in artificial intelligence technologies have widespread and increased the use of artificial intelligence in many areas. The field of he...
Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.
Expert review of hematology
May 24, 2024
BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and chara...
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