AIMC Topic: Sensitivity and Specificity

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Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.

World journal of surgical oncology
OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magnetic resonance imaging (MRI) models in distinguishing benign from malignant breast lesions and explores factors influencing their performance.

Machine learning driven biomarker selection for medical diagnosis.

PloS one
Recent advances in experimental methods have enabled researchers to collect data on thousands of analytes simultaneously. This has led to correlational studies that associated molecular measurements with diseases such as Alzheimer's, Liver, and Gastr...

Artificial intelligence-based detection of dens invaginatus in panoramic radiographs.

BMC oral health
OBJECTIVE: The aim of this study was to automatically detect teeth with dens invaginatus (DI) in panoramic radiographs using deep learning algorithms and to compare the success of the algorithms.

Impact of AI-Generated ADC Maps on Computer-Aided Diagnosis of Prostate Cancer: A Feasibility Study.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the impact of AI-generated apparent diffusion coefficient (ADC) maps on diagnostic performance of a 3D U-Net AI model for prostate cancer (PCa) detection and segmentation at biparametric MRI (bpMRI).

Segmentation of airways and soft tissues on panoramic radiographs using artificial intelligence technology.

BMC oral health
BACKGROUND: Segmentation of airways and soft tissues on panoramic radiographs is a challenging yet crucial task in dental diagnostics, as these regions can often be confused with fractures or other lesions due to superimposition. This study aimed to ...

Detecting Tardive Dyskinesia Using Video-Based Artificial Intelligence.

The Journal of clinical psychiatry
Tardive dyskinesia (TD) is a late-onset adverse effect of dopamine receptor-blocking medications, characterized by involuntary movements primarily affecting the mouth, though other body parts may be involved. Severity of TD varies from mild to debil...

Two birds with one stone: pre-TAVI coronary CT angiography combined with FFR helps screen for coronary stenosis.

BMC medical imaging
OBJECTIVES: Since coronary artery disease (CAD) is a common comorbidity in patients with aortic valve stenosis, invasive coronary angiography (ICA) can be avoided if significant CAD can be screened with the non-invasive coronary CT angiography (cCTA)...

Atrial fibrillation detection via contactless radio monitoring and knowledge transfer.

Nature communications
Atrial fibrillation (AF) has been a prevalent and serious arrhythmia associated with increased morbidity and mortality worldwide. The Electrocardiogram (ECG) is considered as the golden standard for AF diagnosis. However, current ECG is primarily use...

Accuracy of an nnUNet Neural Network for the Automatic Segmentation of Intracranial Aneurysms, Their Parent Vessels, and Major Cerebral Arteries from MRI-TOF.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: The automatic recognition of intracraial aneurysms by means of machine-learning algorithms represents a new frontier for diagnostic and therapeutic goals. Yet, the current algorithms focus solely on the aneurysms and not on th...