AIMC Topic: Sensitivity and Specificity

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Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study.

Journal of stomatology, oral and maxillofacial surgery Oct 31, 2024
OBJECTIVE: The purpose of this study was to investigate the diagnostic performance of a neural network Artificial Intelligence model for the radiographic confirmation of Temporomandibular Joint Osteoarthritis in reference to an experienced radiologis...
Humans Female Cohort Studies Cone-Beam Computed Tomography Temporomandibular Joint Disorders Osteoarthritis Temporomandibular Joint Adult Sensitivity and Specificity Male Middle Aged Deep Learning
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Applying Deep-Learning Algorithm Interpreting Kidney, Ureter, and Bladder (KUB) X-Rays to Detect Colon Cancer.

Journal of imaging informatics in medicine Oct 31, 2024
Early screening is crucial in reducing the mortality of colorectal cancer (CRC). Current screening methods, including fecal occult blood tests (FOBT) and colonoscopy, are primarily limited by low patient compliance and the invasive nature of the proc...
Humans Algorithms Radiographic Image Interpretation, Computer-Assisted Colonic Neoplasms Urinary Bladder Ureter Male Retrospective Studies Middle Aged Female Deep Learning Aged Kidney Sensitivity and Specificity Early Detection of Cancer
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Machine Learning Differentiates Between Benign and Malignant Parotid Tumors With Contrast-Enhanced Ultrasound Features.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons Oct 31, 2024
BACKGROUND: Contrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tumors (BPTs) from malignant parotid tumors (MPTs). Introducing machine learning may enable clinicians to preoperatively diagnose parotid tumors precisel...
Retrospective Studies Diagnosis, Differential Female Humans Male Parotid Neoplasms Aged Machine Learning Middle Aged Adult Ultrasonography Sensitivity and Specificity Support Vector Machine Contrast Media
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A deep learning algorithm that aids visualization of femoral neck fractures and improves physician training.

Injury Oct 31, 2024
PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatment and unfavorable prognosis. Here, we developed a fully automated deep learning model to detect and ...
Humans Algorithms Female Aged Sensitivity and Specificity ROC Curve Male Radiography Femoral Neck Fractures Middle Aged Deep Learning Clinical Competence
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Early Detection of Breast Cancer in MRI Using AI.

Academic radiology Oct 30, 2024
RATIONALE AND OBJECTIVES: To develop and evaluate an AI algorithm that detects breast cancer in MRI scans up to one year before radiologists typically identify it, potentially enhancing early detection in high-risk women.
Middle Aged Artificial Intelligence Image Interpretation, Computer-Assisted Algorithms Adolescent Retrospective Studies Magnetic Resonance Imaging Female Humans Early Detection of Cancer Aged Neural Networks, Computer Aged, 80 and over Young Adult Adult Sensitivity and Specificity Breast Neoplasms
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Machine learning-derived clinical decision algorithm for the diagnosis of hyperfunctioning parathyroid glands in patients with primary hyperparathyroidism.

European radiology Oct 30, 2024
PURPOSE: To train and validate machine learning-derived clinical decision algorithm (CDA) for the diagnosis of hyperfunctioning parathyroid glands using preoperative variables to facilitate surgical planning.
Female Aged Adult Sensitivity and Specificity Male Machine Learning Algorithms Retrospective Studies Clinical Decision-Making Single Photon Emission Computed Tomography Computed Tomography Four-Dimensional Computed Tomography Technetium Tc 99m Sestamibi Middle Aged Radiopharmaceuticals Parathyroidectomy Hyperparathyroidism, Primary Parathyroid Glands Humans
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Real-World Performance of Pneumothorax-Detecting Artificial Intelligence Algorithm and its Impact on Radiologist Reporting Times.

Academic radiology Oct 29, 2024
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) algorithms in radiology capable of detecting urgent findings have gained significant traction in recent years, but the impact of these algorithms on real-world clinical practice remains unclear w...
Female Adult Sensitivity and Specificity Male Middle Aged Radiology Information Systems Radiography, Thoracic Pneumothorax Humans Artificial Intelligence Algorithms Retrospective Studies
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Wearable-Enabled Algorithms for the Estimation of Parkinson's Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 29, 2024
Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus, the ideal home monitoring system should be capable of tracking symptoms continuously despite background noise from daily activities. The goal of thi...
Wearable Electronic Devices Reproducibility of Results Tremor Humans Parkinson Disease Aged Activities of Daily Living Equipment Design Machine Learning Dyskinesias Feasibility Studies Sensitivity and Specificity Video Recording Algorithms Male Monitoring, Ambulatory Middle Aged Accelerometry Female Hypokinesia
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SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.

Journal of imaging informatics in medicine Oct 28, 2024
Timely and precise identification of acute ischemic stroke (AIS) within 4.5 h is imperative for effective treatment decision-making. This study aims to construct a novel network that utilizes limited datasets to recognize AIS patients within this cri...
Ischemic Stroke Thrombolytic Therapy Diffusion Magnetic Resonance Imaging Sensitivity and Specificity Male Middle Aged Magnetic Resonance Imaging Humans Neural Networks, Computer Retrospective Studies Female Aged
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Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography.

European journal of radiology Oct 28, 2024
PURPOSE: To examine the impact of deep learning-augmented contrast enhancement on image quality and diagnostic accuracy of poorly contrasted CT angiography in patients with suspected stroke.
Signal-To-Noise Ratio Computed Tomography Angiography Cerebral Angiography Radiographic Image Enhancement Middle Aged Humans Deep Learning Retrospective Studies Contrast Media Female Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Stroke Aged Sensitivity and Specificity Male
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