AIMC Topic: Sensitivity and Specificity
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Recent progress in tuberculosis diagnosis: insights into blood-based biomarkers and emerging technologies.
Frontiers in cellular and infection microbiology
Jan 1, 2025
Tuberculosis (TB) remains a global health challenge, with timely and accurate diagnosis being critical for effective disease management and control. Recent advancements in the field of TB diagnostics have focused on the identification and utilization...
Cytopathological quantification of NORs using artificial intelligence to oral cancer screening.
Brazilian oral research
Jan 1, 2025
Oral squamous cell carcinoma (OSCC) remains the most prevalent neoplasm of the head and neck. In recent decades, the incidence and prevalence of OSCC have not significantly changed, highlighting the critical need to develop and implement new risk ass...
Comparative analysis of diagnostic performance in mammography: A reader study on the impact of AI assistance.
PloS one
Jan 1, 2025
PURPOSE: This study evaluates the impact of artificial intelligence (AI) assistance on the diagnostic performance of radiologists with varying levels of experience in interpreting mammograms in a Malaysian tertiary referral center, particularly in wo...
Exploring and Identifying Key Factors in Predicting Dyslexia in Children: Advanced Machine Learning Algorithms From Screening to Diagnosis.
Clinical psychology & psychotherapy
Jan 1, 2025
INTRODUCTION: The current study aimed to develop and validate a machine learning (ML)-based predictive models for early dyslexia detection in children by integrating neurocognitive, linguistic and behavioural predictors.
Artificial Intelligence in Endoscopy for Predicting Helicobacter pylori Infection: A Systematic Review and Meta-Analysis.
Helicobacter
Jan 1, 2025
PURPOSE: This meta-analysis aimed to assess the diagnostic performance of artificial intelligence (AI) based on endoscopy for detecting Helicobacter pylori (H. pylori) infection.
Optimizing Stroke Detection Using Evidential Networks and Uncertainty-Based Refinement.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 1, 2025
Evaluating neurological impairments post-stroke is essential for assessing treatment efficacy and managing subsequent disabilities. Conventional clinical assessment methods depend largely on clinicians' visual and physical evaluations, resulting in c...
A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.
The western journal of emergency medicine
Jan 1, 2025
INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe devices include many ubiquitous items in emergency care, such as vascular access devices, ventilators, infusion pumps, video laryngoscopes, pulse oxim...
Deep Learning-assisted Diagnosis of Extrahepatic Common Bile Duct Obstruction Using MRCP Imaging and Clinical Parameters.
Current medical imaging
Jan 1, 2025
BACKGROUND: Extrahepatic Common Bile Duct Obstruction (EHBDO) is a serious condition that requires accurate diagnosis for effective treatment. Magnetic Resonance Cholangiopancreatography (MRCP) is a widely used noninvasive imaging technique for visua...
Advanced CNN Architecture for Brain Tumor Segmentation and Classification using BraTS-GOAT 2024 Dataset.
Current medical imaging
Jan 1, 2025
BACKGROUND: The BraTS Generalizability Across Tumors (BraTS-GoAT) initiative addresses the critical need for robust and generalizable models in brain tumor segmentation. Despite advancements in automated segmentation techniques, the variability in tu...
Deep learning can detect elbow disease in dogs screened for elbow dysplasia.
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Jan 1, 2025
Medical image analysis based on deep learning is a rapidly advancing field in veterinary diagnostics. The aim of this retrospective diagnostic accuracy study was to develop and assess a convolutional neural network (CNN, EfficientNet) to evaluate elb...
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