AIMC Topic: Sensitivity and Specificity
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Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias.
Epilepsy research
Apr 3, 2024
PURPOSE: Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD det...
Deep Learning in High-Resolution Anoscopy: Assessing the Impact of Staining and Therapeutic Manipulation on Automated Detection of Anal Cancer Precursors.
Clinical and translational gastroenterology
Apr 1, 2024
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell carcinoma (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising res...
Male
Middle Aged
Deep Learning
Staining and Labeling
Anal Canal
Aged
Predictive Value of Tests
Acetic Acid
Adult
Precancerous Conditions
Proctoscopy
Humans
Neural Networks, Computer
Squamous Intraepithelial Lesions
Sensitivity and Specificity
Anus Neoplasms
Algorithms
Female
Carcinoma, Squamous Cell
Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.
Journal of dentistry
Mar 30, 2024
OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the car...
The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country.
Clinical radiology
Mar 29, 2024
AIM: We aimed to investigate the efficiency and accuracy of an artificial intelligence (AI) algorithm for detecting interval cancers in a middle-income country's national screening program.
Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett's esophagus: a tandem randomized and video trial.
Endoscopy
Mar 28, 2024
BACKGROUND: This study evaluated the effect of an artificial intelligence (AI)-based clinical decision support system on the performance and diagnostic confidence of endoscopists in their assessment of Barrett's esophagus (BE).
Automatic ARDS surveillance with chest X-ray recognition using convolutional neural networks.
Journal of critical care
Mar 28, 2024
OBJECTIVE: This study aims to design, validate and assess the accuracy a deep learning model capable of differentiation Chest X-Rays between pneumonia, acute respiratory distress syndrome (ARDS) and normal lungs.
Machine Learning Approaches to Identify Affected Brain Regions in Movement Disorders Using MRI Data: A Systematic Review and Diagnostic Meta-analysis.
Journal of magnetic resonance imaging : JMRI
Mar 27, 2024
BACKGROUND: Movement disorders such as Parkinson's disease are associated with structural and functional changes in specific brain regions. Advanced magnetic resonance imaging (MRI) techniques combined with machine learning (ML) are promising tools f...
Cost-Effectiveness of Artificial Intelligence-Based Opportunistic Compression Fracture Screening of Existing Radiographs.
Journal of the American College of Radiology : JACR
Mar 26, 2024
PURPOSE: Osteoporotic vertebral compression fractures (OVCFs) are a highly prevalent source of morbidity and mortality, and preventive treatment has been demonstrated to be both effective and cost effective. To take advantage of the information avail...
Accuracy of machine learning in the diagnosis of odontogenic cysts and tumors: a systematic review and meta-analysis.
Oral radiology
Mar 26, 2024
BACKGROUND: The recent impact of artificial intelligence in diagnostic services has been enormous. Machine learning tools offer an innovative alternative to diagnose cysts and tumors radiographically that pose certain challenges due to the near simil...
Application of deep learning radiomics in oral squamous cell carcinoma-Extracting more information from medical images using advanced feature analysis.
Journal of stomatology, oral and maxillofacial surgery
Mar 26, 2024
OBJECTIVE: To conduct a systematic review with meta-analyses to assess the recent scientific literature addressing the application of deep learning radiomics in oral squamous cell carcinoma (OSCC).
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