AIMC Topic: Sensitivity and Specificity

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Artificial intelligence in predicting chronic kidney disease prognosis. A systematic review and meta-analysis.

Renal failure Dec 11, 2024
BACKGROUND: Chronic kidney disease (CKD) is a common condition that can lead to serious health complications. Artificial Intelligence (AI) has shown the potential to improve the prediction of CKD progression, offering increased accuracy over traditio...
Humans Artificial Intelligence Prognosis Renal Insufficiency, Chronic Sensitivity and Specificity Disease Progression
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Assessment of image quality on the diagnostic performance of clinicians and deep learning models: Cross-sectional comparative reader study.

Journal of the European Academy of Dermatology and Venereology : JEADV Dec 10, 2024
BACKGROUND: Skin cancer is a prevalent and clinically significant condition, with early and accurate diagnosis being crucial for improved patient outcomes. Dermoscopy and artificial intelligence (AI) hold promise in enhancing diagnostic accuracy. How...
Dermoscopy Sensitivity and Specificity Cross-Sectional Studies Deep Learning Humans Neural Networks, Computer Skin Neoplasms
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Evaluating the efficacy of AI systems in diabetic retinopathy detection: A comparative analysis of Mona DR and IDx-DR.

Acta ophthalmologica Dec 10, 2024
PURPOSE: To compare two artificial intelligence (AI)-based Automated Diabetic Retinopathy Image Assessment (ARIA) softwares in terms of concordance with specialist human graders and referable diabetic retinopathy (DR) diagnostic capacity.
Humans Diabetic Retinopathy Reproducibility of Results Aged Artificial Intelligence Adult Male Retrospective Studies Sensitivity and Specificity Middle Aged Female Photography
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Convolutional neural networks for automatic MR classification of myocardial iron overload in thalassemia major patients.

European radiology Dec 10, 2024
OBJECTIVES: To develop a deep-learning model for supervised classification of myocardial iron overload (MIO) from magnitude T2* multi-echo MR images.
Young Adult Iron Overload Adult Image Interpretation, Computer-Assisted Sensitivity and Specificity Humans Adolescent Neural Networks, Computer Magnetic Resonance Imaging Child Retrospective Studies Male beta-Thalassemia Deep Learning Female Convolutional Neural Networks
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A novel AI model for detecting periapical lesion on CBCT: CBCT-SAM.

Journal of dentistry Dec 10, 2024
OBJECTIVES: Periapical lesions are not always evident on radiographic scans. Sometimes, asymptomatic or initial periapical lesions on cone-beam computed tomography (CBCT) could be missed by inexperienced dentists, especially when the scan has a large...
Sensitivity and Specificity Humans Artificial Intelligence Cone-Beam Computed Tomography Algorithms Periapical Diseases
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Diagnosis of infections using artificial intelligence techniques versus standard microscopy in a reference laboratory.

Journal of clinical microbiology Dec 10, 2024
Diagnosing malaria using standard techniques is time-consuming. With limited staffing in many laboratories, this may lead to delays in reporting. Innovative technologies are changing the diagnostic landscape and may help alleviate staffing shortages....
Plasmodium falciparum Malaria Microscopy Malaria, Falciparum Parasitemia Artificial Intelligence Automation, Laboratory Sensitivity and Specificity Humans
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Integration of AI-Assisted in Digital Cervical Cytology Training: A Comparative Study.

Cytopathology : official journal of the British Society for Clinical Cytology Dec 8, 2024
OBJECTIVE: This study aimed to investigate the supporting role of artificial intelligence (AI) in digital cervical cytology training.
Cervix Uteri Cytodiagnosis Sensitivity and Specificity Uterine Cervical Neoplasms Vaginal Smears Female Adult Humans Artificial Intelligence
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Development and Validation of a Deep Learning System to Differentiate HER2-Zero, HER2-Low, and HER2-Positive Breast Cancer Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI Dec 6, 2024
BACKGROUND: Previous studies explored MRI-based radiomic features for differentiating between human epidermal growth factor receptor 2 (HER2)-zero, HER2-low, and HER2-positive breast cancer, but deep learning's effectiveness is uncertain.
Contrast Media Magnetic Resonance Imaging Breast Middle Aged Deep Learning ROC Curve Image Interpretation, Computer-Assisted Receptor, ErbB-2 Retrospective Studies Female Reproducibility of Results Sensitivity and Specificity Breast Neoplasms Aged Adult Humans
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Detection of three-rooted mandibular first molars on panoramic radiographs using deep learning.

Scientific reports Dec 5, 2024
This study aimed to develop a deep learning system for the detection of three-rooted mandibular first molars (MFMs) on panoramic radiographs and to assess its diagnostic performance. Panoramic radiographs, together with cone beam computed tomographic...
Neural Networks, Computer Retrospective Studies Female Aged Humans Adolescent ROC Curve Cone-Beam Computed Tomography Male Molar Middle Aged Tooth Root Deep Learning Young Adult Mandible Adult Radiography, Panoramic Sensitivity and Specificity
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Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

BMC musculoskeletal disorders Dec 4, 2024
BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a decrease in bone density and a loss of the quality of the bone structure. The use of deep learning in the prediction of osteoporosis can provide a non-in...
Osteoporosis Sensitivity and Specificity Deep Learning Predictive Value of Tests Humans Neural Networks, Computer Bone Density
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