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Factors for increasing positive predictive value of pneumothorax detection on chest radiographs using artificial intelligence.
Scientific reports
Aug 23, 2024
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...
Evaluation of perceived urgency from single-trial EEG data elicited by upper-body vibration feedback using deep learning.
Scientific reports
Aug 23, 2024
Notification systems that convey urgency without adding cognitive burden are crucial in human-computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing ...
Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.
Journal of computer assisted tomography
Aug 22, 2024
OBJECTIVE: This study aims to evaluate, on one MRI vendor's platform, the impact of deep learning (DL)-based reconstruction techniques on MRI radiomic features compared to conventional image reconstruction techniques.
Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study.
Journal of magnetic resonance imaging : JMRI
Aug 22, 2024
BACKGROUND: Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized select...
Development of an equation to predict delta bilirubin levels using machine learning.
Clinica chimica acta; international journal of clinical chemistry
Aug 22, 2024
OBJECTIVE: Delta bilirubin (albumin-covalently bound bilirubin) may provide important clinical utility in identifying impaired hepatic excretion of conjugated bilirubin, but it cannot be measured in real-time for diagnostic purposes in clinical labor...
Investigating the role of artificial intelligence in predicting perceived dysphonia level.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Aug 22, 2024
PURPOSE: This study aims to investigate the role of one of these models in the field of voice pathology and compare its performance in distinguishing the perceived dysphonia level.
Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach.
NeuroImage
Aug 22, 2024
Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early s...
Artificial Intelligence-Assisted Speech Therapy for /ɹ/: A Single-Case Experimental Study.
American journal of speech-language pathology
Aug 22, 2024
PURPOSE: This feasibility trial describes changes in rhotic production in residual speech sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted motor-based intervention with ChainingAI, a version of Speech Motor...
Advanced Sensing System for Sleep Bruxism across Multiple Postures via EMG and Machine Learning.
Sensors (Basel, Switzerland)
Aug 22, 2024
Diagnosis of bruxism is challenging because not all contractions of the masticatory muscles can be classified as bruxism. Conventional methods for sleep bruxism detection vary in effectiveness. Some provide objective data through EMG, ECG, or EEG; ot...
Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study.
Scientific reports
Aug 22, 2024
A critical problem that Emergency Departments (EDs) must address is overcrowding, as it causes extended waiting times and increased patient dissatisfaction, both of which are immediately linked to a greater number of patients who leave the ED early, ...
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