AIMC Topic: Sensitivity and Specificity

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Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

Cardiovascular and interventional radiology Mar 26, 2024
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.
Algorithms Retrospective Studies Female Aged Adult Sensitivity and Specificity Male Middle Aged Humans Artificial Intelligence Angiography, Digital Subtraction Radiographic Image Interpretation, Computer-Assisted Mesenteric Arteries Embolization, Therapeutic Celiac Artery Gastrointestinal Hemorrhage
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Convolutional neural network for identifying common bile duct stones based on magnetic resonance cholangiopancreatography.

Clinical radiology Mar 24, 2024
AIMS: To develop an auto-categorization system based on machine learning for three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) to detect choledocholithiasis from healthy and symptomatic individuals.
Imaging, Three-Dimensional Choledocholithiasis Humans Gallstones Neural Networks, Computer Prospective Studies Cholangiopancreatography, Magnetic Resonance Sensitivity and Specificity Common Bile Duct Machine Learning Female Male Aged Middle Aged Adult
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Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association Mar 21, 2024
The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical examination. Evaluating pressure injuries is time consuming, energy intensive, and inconsistent. Most of...
Detection Algorithms Sensitivity and Specificity Image Processing, Computer-Assisted Generative Artificial Intelligence Humans Telemedicine Digital Health Video Recording Photography Pressure Ulcer Large Language Models
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A deep learning method to identify and localize large-vessel occlusions from cerebral digital subtraction angiography.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Mar 20, 2024
BACKGROUND AND PURPOSE: An essential step during endovascular thrombectomy is identifying the occluded arterial vessel on a cerebral digital subtraction angiogram (DSA). We developed an algorithm that can detect and localize the position of occlusion...
Male Middle Aged Deep Learning Angiography, Digital Subtraction Cerebral Angiography Retrospective Studies Female Aged Sensitivity and Specificity Humans Algorithms
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How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review.

Clinical radiology Mar 19, 2024
BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy ...
Central Nervous System Neoplasms Astrocytoma Diagnosis, Differential Brain Neoplasms Glioblastoma Deep Learning Radiologists Lymphoma Magnetic Resonance Imaging Humans Machine Learning Sensitivity and Specificity
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Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections.

Microbiology spectrum Mar 18, 2024
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could aid the diagnosis of acute respiratory infections (ARIs) owing to its affordability and high-throughput capacity. MALDI-TOF MS has been proposed for use...
Sensitivity and Specificity Male Middle Aged Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Female SARS-CoV-2 Adult Respiratory Tract Infections Nasopharynx Kazakhstan Humans Machine Learning COVID-19
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Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h.

European radiology Mar 15, 2024
OBJECTIVES: We aimed to develop machine learning (ML) models based on diffusion- and perfusion-weighted imaging fusion (DP fusion) for identifying stroke within 4.5 h, to compare them with DWI- and/or PWI-based ML models, and to construct an automati...
Male Middle Aged Time Factors Multimodal Imaging Stroke Image Interpretation, Computer-Assisted Diffusion Magnetic Resonance Imaging Machine Learning Female Aged Humans Sensitivity and Specificity
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Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis.

Clinical radiology Mar 15, 2024
AIM: The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis.
Ovary Reproducibility of Results Humans Sensitivity and Specificity Machine Learning Diagnosis, Differential Female Ovarian Neoplasms
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Editorial Commentary: Evaluation for Cartilage Lesions on Magnetic Resonance Imaging Continues to Improve: Artificial Intelligence Applications May Result in Higher Sensitivity and Specificity.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association Mar 13, 2024
Accurate detection of cartilage lesions of the knee is required to offer patient-specific care and can alter surgical intervention options. To date, diagnostic arthroscopy remains the gold standard yet often requires the need for staged operative pro...
Artificial Intelligence Sensitivity and Specificity Magnetic Resonance Imaging Knee Joint Humans Cartilage Diseases Cartilage, Articular
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Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR).

Abdominal radiology (New York) Mar 12, 2024
PURPOSE: Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep lear...
Aged Aged, 80 and over Adult Sensitivity and Specificity Algorithms Retrospective Studies Tomography, X-Ray Computed Humans Female Radiation Dosage Radiography, Abdominal Urolithiasis Urinary Calculi Male Middle Aged Deep Learning Radiographic Image Interpretation, Computer-Assisted
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