AIMC Topic: Sensitivity and Specificity
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Machine learning models for differential diagnosing HER2-low breast cancer: A radiomics approach.
Medicine
Aug 16, 2024
To develop machine learning models based on preoperative dynamic enhanced magnetic resonance imaging (DCE-MRI) radiomics and to explore their potential prognostic value in the differential diagnosis of human epidermal growth factor receptor 2 (HER2)-...
Hybrid Artificial Intelligence Solution Combining Convolutional Neural Network and Analytical Approach Showed Higher Accuracy in A-lines Detection on Lung Ultrasound in Thoracic Surgery Patients Compared with Radiology Resident.
Neuro endocrinology letters
Aug 12, 2024
OBJECTIVES: Lung ultrasound reduces the number of chest X-rays after thoracic surgery and thus the radiation. COVID-19 pandemic has accelerated research in lung ultrasound artifacts detection using artificial intelligence. This study evaluates the ac...
Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.
Health technology assessment (Winchester, England)
Aug 1, 2024
BACKGROUND: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intellig...
Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.
Radiology
Aug 1, 2024
Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. Purpose To evaluate AI localizations of interval cancers (ICs) on screening mammograms by IC category...
Using AI to Identify Unremarkable Chest Radiographs for Automatic Reporting.
Radiology
Aug 1, 2024
Background Radiology practices have a high volume of unremarkable chest radiographs and artificial intelligence (AI) could possibly improve workflow by providing an automatic report. Purpose To estimate the proportion of unremarkable chest radiograph...
Next generation mycological diagnosis: Artificial intelligence-based classifier of the presence of Malassezia yeasts in tape strip samples.
Mycoses
Aug 1, 2024
BACKGROUND: Malassezia yeasts are almost universally present on human skin worldwide. While they can cause diseases such as pityriasis versicolor, their implication in skin homeostasis and pathophysiology of other dermatoses is still unclear. Their a...
Can we screen opportunistically for low bone mineral density using CT scans of the shoulder and artificial intelligence?
The British journal of radiology
Aug 1, 2024
OBJECTIVE: To evaluate whether the CT attenuation of bones seen on shoulder CT scans could be used to predict low bone mineral density (BMD) (osteopenia/osteoporosis), and to compare the performance of two machine learning models to predict low BMD.
[Diagnostic Value of Micropure Imaging Combined with Strain Elastography in Correcting Artificial Intelligence S-Detect Technology for Benign and Malignant Breast Complex Cystic and Solid Masses].
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Jul 30, 2024
OBJECTIVE: To explore the diagnostic value of micropure imaging (MI) combined with strain elastography (SE) in correcting artificial intelligence (AI) S-Detect technology for benign and malignant breast complex cystic and solid masses.
Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.
World journal of gastroenterology
Jul 7, 2024
BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease (CD) is a challenge in clinical practice.
HRV-based Monitoring of Neonatal Seizures with Machine Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
With the rapid development of machine learning (ML) in biomedical signal processing, ML-based neonatal seizure detection using heart rate variability (HRV) parameters extracted from the electrocardiogram (ECG) has gained increasing interest. In this ...
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