AIMC Topic: Sensitivity and Specificity
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Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.
PloS one
Dec 17, 2024
Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications. This study aimed to evaluate fundus photographs using artificial intelligence to explore the relat...
Humans
Severity of Illness Index
Diabetic Retinopathy
Liver Cirrhosis
Artificial Intelligence
Sensitivity and Specificity
Glycated Hemoglobin
Cross-Sectional Studies
Software
Fundus Oculi
Male
Female
Protective Factors
Risk Factors
Middle Aged
Cholinesterases
Non-alcoholic Fatty Liver Disease
Japan
Image Interpretation, Computer-Assisted
Photography
SMART: Development and Application of a Multimodal Multi-organ Trauma Screening Model for Abdominal Injuries in Emergency Settings.
Academic radiology
Dec 16, 2024
RATIONALE AND OBJECTIVES: Effective trauma care in emergency departments necessitates rapid diagnosis by interdisciplinary teams using various medical data. This study constructed a multimodal diagnostic model for abdominal trauma using deep learning...
A Fusion Model of MRI Deep Transfer Learning and Radiomics for Discriminating between Pilocytic Astrocytoma and Adamantinomatous Craniopharyngioma.
Academic radiology
Dec 16, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a fusion model combining MRI deep transfer learning (DTL) and radiomics for discriminating between pilocytic astrocytoma (PA) and adamantinomatous craniopharyngioma (ACP) in the sella...
Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.
Annals of laboratory medicine
Dec 16, 2024
BACKGROUND: Urinalysis, an essential diagnostic tool, faces challenges in terms of standardization and accuracy. The use of artificial intelligence (AI) with mobile technology can potentially solve these challenges. Therefore, we investigated the eff...
Diagnostic performance of neural network algorithms in skull fracture detection on CT scans: a systematic review and meta-analysis.
Emergency radiology
Dec 16, 2024
BACKGROUND AND AIM: The potential intricacy of skull fractures as well as the complexity of underlying anatomy poses diagnostic hurdles for radiologists evaluating computed tomography (CT) scans. The necessity for automated diagnostic tools has been ...
Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method.
Magnetic resonance imaging
Dec 14, 2024
PURPOSE: To develop a multi-parametric MRI model for the prediction of molecular subtypes of breast cancer using five types of breast cancer preoperative MRI images.
Deep learning-assistance significantly increases the detection sensitivity of neurosurgery residents for intracranial aneurysms in subarachnoid hemorrhage.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Dec 13, 2024
OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM) in improving the sensitivity of neurosurgery residents to detect intracranial aneurysms on CT angiography (CTA) in patients with aneurysmal subarach...
Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.
International journal of oral and maxillofacial surgery
Dec 12, 2024
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...
ARTIFICIAL INTELLIGENCE PLATFORMS IN DENTAL CARIES DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS.
The journal of evidence-based dental practice
Dec 12, 2024
OBJECTIVES: To assess Artificial Intelligence (AI) platforms, machine learning methodologies and associated accuracies used in detecting dental caries from clinical images and dental radiographs.
Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.
La Radiologia medica
Dec 12, 2024
PURPOSE: Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (C...
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