AIMC Topic: Sensitivity and Specificity

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Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

Eye (London, England) Mar 11, 2024
BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people with diabetes. The timely diagnosis and treatment of DR are essential in preventing vision loss. Non-mydriatic fundus cameras and artificial intelligenc...
Male Middle Aged Photography Adult Sensitivity and Specificity Humans Female Diabetic Retinopathy Reproducibility of Results Artificial Intelligence Aged
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Real-world artificial intelligence-based interpretation of fundus imaging as part of an eyewear prescription renewal protocol.

Journal francais d'ophtalmologie Mar 8, 2024
OBJECTIVE: A real-world evaluation of the diagnostic accuracy of the Opthai® software for artificial intelligence-based detection of fundus image abnormalities in the context of the French eyewear prescription renewal protocol (RNO).
Humans Artificial Intelligence Software Retrospective Studies Female Fundus Oculi Ophthalmologists Middle Aged France Young Adult Adult Retinal Diseases Adolescent Child Sensitivity and Specificity Male
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Automated Spontaneous Echo Contrast Detection Using a Multisequence Attention Convolutional Neural Network.

Ultrasound in medicine & biology Mar 8, 2024
OBJECTIVE: Spontaneous echo contrast (SEC) is a vascular ultrasound finding associated with increased thromboembolism risk. However, identification requires expert determination and clinician time to report. We developed a deep learning model that ca...
Ultrasonography Femoral Vein Sensitivity and Specificity Male Deep Learning Retrospective Studies Female Humans Neural Networks, Computer
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Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

European radiology Mar 7, 2024
OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between ischemic cardiomyopathy (ICM) and non-ischemic cardiomyopathy (NICM) on non-contrast cardiovascular magnetic resonance (CMR).
Male Middle Aged Diagnosis, Differential Reproducibility of Results Aged Sensitivity and Specificity Myocardial Ischemia Cardiomyopathies Magnetic Resonance Imaging, Cine Humans Machine Learning Retrospective Studies Female
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Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis.

Journal of imaging informatics in medicine Mar 4, 2024
Due to the increasing interest in the use of artificial intelligence (AI) algorithms in hepatocellular carcinoma detection, we performed a systematic review and meta-analysis to pool the data on diagnostic performance metrics of AI and to compare the...
Humans Artificial Intelligence Algorithms Carcinoma, Hepatocellular Sensitivity and Specificity Liver Neoplasms
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Diagnostic Accuracy of Artificial Intelligence-Based Automated Diabetic Retinopathy Screening in Real-World Settings: A Systematic Review and Meta-Analysis.

American journal of ophthalmology Mar 2, 2024
PURPOSE: To evaluate the diagnostic accuracy of artificial intelligence (AI)-based automated diabetic retinopathy (DR) screening in real-world settings.
Artificial Intelligence Algorithms Humans Reproducibility of Results Diabetic Retinopathy Sensitivity and Specificity Mass Screening
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Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

Clinical oral investigations Mar 2, 2024
OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aime...
Diagnostic Imaging Temporomandibular Joint Disorders Diagnostic Tests, Routine Machine Learning Sensitivity and Specificity Radiography Humans
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Artificial intelligence-based diagnosis of standard endoscopic ultrasonography scanning sites in the biliopancreatic system: a multicenter retrospective study.

International journal of surgery (London, England) Mar 1, 2024
BACKGROUND: There are challenges for beginners to identify standard biliopancreatic system anatomical sites on endoscopic ultrasonography (EUS) images. Therefore, the authors aimed to develop a convolutional neural network (CNN)-based model to identi...
Retrospective Studies Sensitivity and Specificity Humans Endosonography Neural Networks, Computer Artificial Intelligence
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Editorial for "Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI-RADS v2.1 Score ≥3".

Journal of magnetic resonance imaging : JMRI Feb 29, 2024
Male Humans Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Machine Learning Algorithms Prostatic Neoplasms Reproducibility of Results Sensitivity and Specificity
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The effect of incorporating domain knowledge with deep learning in identifying benign and malignant gastric whitish lesions: A retrospective study.

Journal of gastroenterology and hepatology Feb 27, 2024
BACKGROUND AND AIM: Early whitish gastric neoplasms can be easily misdiagnosed; differential diagnosis of gastric whitish lesions remains a challenge. We aim to build a deep learning (DL) model to diagnose whitish gastric neoplasms and explore the ef...
Sensitivity and Specificity Deep Learning Diagnosis, Differential Humans Retrospective Studies Algorithms Stomach Neoplasms
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