AIMC Topic: Sensitivity and Specificity

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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.
Early Detection of Cancer Image Interpretation, Computer-Assisted Female Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Adolescent Magnetic Resonance Imaging Humans Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies
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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.
Machine Learning Algorithms Retrospective Studies Clinical Decision-Making Female Humans Single Photon Emission Computed Tomography Computed Tomography Middle Aged Four-Dimensional Computed Tomography Radiopharmaceuticals Technetium Tc 99m Sestamibi Parathyroidectomy Hyperparathyroidism, Primary Parathyroid Glands Aged Adult Sensitivity and Specificity Male
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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...
Retrospective Studies Female Adult Sensitivity and Specificity Male Humans Artificial Intelligence Algorithms Middle Aged Radiology Information Systems Radiography, Thoracic Pneumothorax
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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...
Dyskinesias Wearable Electronic Devices Reproducibility of Results Humans Parkinson Disease Video Recording Aged Equipment Design Machine Learning Monitoring, Ambulatory Sensitivity and Specificity Feasibility Studies Algorithms Accelerometry Male Activities of Daily Living Female Hypokinesia Middle Aged Tremor
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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...
Humans Neural Networks, Computer Middle Aged Retrospective Studies Magnetic Resonance Imaging Female Ischemic Stroke Aged Thrombolytic Therapy Sensitivity and Specificity Diffusion Magnetic Resonance Imaging Male
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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.
Reproducibility of Results Deep Learning Aged Computed Tomography Angiography Humans Sensitivity and Specificity Contrast Media Cerebral Angiography Retrospective Studies Male Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Female Middle Aged Stroke Signal-To-Noise Ratio
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Development and Evaluation of a Convolutional Neural Network for Microscopic Diagnosis Between Pleomorphic Adenoma and Carcinoma Ex-Pleomorphic Adenoma.

Head & neck Oct 27, 2024
AIMS: To develop a model capable of distinguishing carcinoma ex-pleomorphic adenoma from pleomorphic adenoma using a convolutional neural network architecture.
Carcinoma Salivary Gland Neoplasms Adenoma, Pleomorphic Middle Aged Humans Brazil Neural Networks, Computer Convolutional Neural Networks Female Cohort Studies Aged Diagnosis, Differential Adult Sensitivity and Specificity Male
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Development and Validation of Machine Learning Models for Predicting Tumor Progression in OSCC.

Oral diseases Oct 27, 2024
OBJECTIVES: Development of a prediction model using machine learning (ML) method for tumor progression in oral squamous cell carcinoma (OSCC) patients would provide risk estimation for individual patient outcomes.
Risk Assessment Disease Progression Logistic Models Mouth Neoplasms Humans Machine Learning Algorithms Female Aged Carcinoma, Squamous Cell Adult Sensitivity and Specificity Male Middle Aged
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Evaluation of a deep learning-based software to automatically detect and quantify breast arterial calcifications on digital mammogram.

Diagnostic and interventional imaging Oct 26, 2024
PURPOSE: The purpose of this study was to evaluate an artificial intelligence (AI) software that automatically detects and quantifies breast arterial calcifications (BAC).
Mammography Radiographic Image Interpretation, Computer-Assisted Breast Vascular Calcification Breast Diseases Humans Software Aged, 80 and over Adult Sensitivity and Specificity Middle Aged Deep Learning Retrospective Studies Tomography, X-Ray Computed Female Aged
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Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Obesity surgery Oct 25, 2024
PURPOSE: Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited for patients with severe obesity and nonalcoholic fatty liver disease (NAFLD). We developed machine learning (ML) models to predict significant liver...
Humans Machine Learning Prospective Studies Female Adult Predictive Value of Tests Biopsy Non-alcoholic Fatty Liver Disease Bariatric Surgery Sensitivity and Specificity Obesity, Morbid Male Middle Aged Liver Cirrhosis Liver
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