AIMC Topic: Sensitivity and Specificity

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Image-based AI diagnostic performance for fatty liver: a systematic review and meta-analysis.

BMC medical imaging Dec 11, 2023
BACKGROUND: The gold standard to diagnose fatty liver is pathology. Recently, image-based artificial intelligence (AI) has been found to have high diagnostic performance. We systematically reviewed studies of image-based AI in the diagnosis of fatty ...
ROC Curve Fatty Liver Magnetic Resonance Imaging Artificial Intelligence Sensitivity and Specificity Humans
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Deep Learning-Based Synthetic TOF-MRA Generation Using Time-Resolved MRA in Fast Stroke Imaging.

AJNR. American journal of neuroradiology Dec 11, 2023
BACKGROUND AND PURPOSE: Time-resolved MRA enables collateral evaluation in acute ischemic stroke with large-vessel occlusion; however, a low SNR and spatial resolution impede the diagnosis of vascular occlusion. We developed a CycleGAN-based deep lea...
Retrospective Studies Sensitivity and Specificity Deep Learning Imaging, Three-Dimensional Humans Ischemic Stroke Stroke Magnetic Resonance Angiography
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Applicability and robustness of an artificial intelligence-based assessment for Greulich and Pyle bone age in a German cohort.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin Dec 8, 2023
PURPOSE: The determination of bone age (BA) based on the hand and wrist, using the 70-year-old Greulich and Pyle (G&P) atlas, remains a widely employed practice in various institutions today. However, a more recent approach utilizing artificial intel...
Age Determination by Skeleton Hand Bones Child Reference Values Germany Humans Artificial Intelligence Software Retrospective Studies Male Female Cohort Studies Adolescent Sensitivity and Specificity Child, Preschool
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The automatic diagnosis artificial intelligence system for preoperative magnetic resonance imaging of uterine sarcoma.

Journal of gynecologic oncology Dec 7, 2023
OBJECTIVE: Magnetic resonance imaging (MRI) is efficient for the diagnosis of preoperative uterine sarcoma; however, misdiagnoses may occur. In this study, we developed a new artificial intelligence (AI) system to overcome the limitations of requirin...
Middle Aged Female Magnetic Resonance Imaging Adult Uterine Neoplasms Sarcoma Humans Sensitivity and Specificity Neural Networks, Computer Artificial Intelligence
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Can artificial intelligence replace endoscopists when assessing mucosal healing in ulcerative colitis? A systematic review and diagnostic test accuracy meta-analysis.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Dec 5, 2023
BACKGROUNDS AND AIMS: Mucosal healing (MH) in inflammatory bowel diseases (IBD) is an important landmark for clinical decision making. Artificial intelligence systems (AI) that automatically deliver the grade of endoscopic inflammation may solve mode...
Artificial Intelligence Sensitivity and Specificity Colonoscopy Colitis, Ulcerative Intestinal Mucosa Deep Learning Wound Healing Humans
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Deep learning approach for discrimination of liver lesions using nine time-phase images of contrast-enhanced ultrasound.

Journal of medical ultrasonics (2001) Dec 5, 2023
PURPOSE: Contrast-enhanced ultrasound (CEUS) shows different enhancement patterns depending on the time after administration of the contrast agent. The aim of this study was to evaluate the diagnostic performance of liver nodule characterization usin...
Ferric Compounds Image Enhancement Deep Learning Ultrasonography Liver Neoplasms Oxides Iron Carcinoma, Hepatocellular Contrast Media Humans Prospective Studies Sensitivity and Specificity
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Machine Learning Methods Based on CT Features Differentiate G1/G2 From G3 Pancreatic Neuroendocrine Tumors.

Academic radiology Dec 4, 2023
RATIONALE AND OBJECTIVES: To identify CT features for distinguishing grade 1 (G1)/grade 2 (G2) from grade 3 (G3) pancreatic neuroendocrine tumors (PNETs) using different machine learning (ML) methods.
Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Neuroendocrine Tumors Adult Retrospective Studies Sensitivity and Specificity Humans Diagnosis, Differential Female Tomography, X-Ray Computed Machine Learning Male Pancreatic Neoplasms Aged Algorithms Middle Aged Support Vector Machine
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Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.

Biomedical engineering online Dec 4, 2023
BACKGROUND: This systematic review and meta-analysis were conducted to objectively evaluate the evidence of machine learning (ML) in the patient diagnosis of Intracranial Hemorrhage (ICH) on computed tomography (CT) scans.
Humans Machine Learning Algorithms Prospective Studies Retrospective Studies Sensitivity and Specificity Diagnostic Tests, Routine
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Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features.

Journal of the Formosan Medical Association = Taiwan yi zhi Dec 2, 2023
BACKGROUND: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.
Gene-Environment Interaction Mitochondrial Precursor Protein Import Complex Proteins Polymorphism, Single Nucleotide Support Vector Machine Alzheimer Disease Female Aged Aged, 80 and over Case-Control Studies Humans ROC Curve Sensitivity and Specificity Neural Networks, Computer Male Machine Learning
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Diagnostic accuracy of artificial intelligence in detecting retinitis pigmentosa: A systematic review and meta-analysis.

Survey of ophthalmology Dec 1, 2023
Retinitis pigmentosa (RP) is often undetected in its early stages. Artificial intelligence (AI) has emerged as a promising tool in medical diagnostics. Therefore, we conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy ...
Humans Artificial Intelligence ROC Curve Tomography, Optical Coherence Diagnostic Techniques, Ophthalmological Retinitis Pigmentosa Algorithms Reproducibility of Results Sensitivity and Specificity
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