AIMC Topic: Sensitivity and Specificity

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Rapid detection of kidney disease based on urine surface-enhanced Raman spectroscopy and principal components analysis-support vector machine/random forests.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Immunoglobulin A nephropathy (IgAN) and idiopathic membranous nephropathy (IMN) are the most prevalent primary glomerulonephritis (PGN) subtypes and can lead to end-stage renal disease. Conventional diagnostic methods in certain aspects are often lim...

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...

Radiological evaluation and clinical implications of deep learning- and MRI-based synthetic CT for the assessment of cervical spine injuries.

European radiology
OBJECTIVE: Efficient evaluation of soft tissues and bony structures following cervical spine trauma is critical. We sought to evaluate the diagnostic validity of magnetic resonance imaging (MRI)-based synthetic CT (sCT) compared with conventional com...

Evaluation of amyloid PET positivity using machine learning on F-FDG PET images.

Japanese journal of radiology
BACKGROUND: Since the approval of disease-modifying drugs for Alzheimer's disease, the demand for amyloid positron emission tomography (PET) scans, which are crucial for determining treatment eligibility, is expected to increase significantly. We thu...

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...

Artificial intelligence for early detection of lung cancer in GPs' clinical notes: a retrospective observational cohort study.

The British journal of general practice : the journal of the Royal College of General Practitioners
BACKGROUND: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in...

Predicting Gene Comutation of EGFR and TP53 by Radiomics and Deep Learning in Patients With Lung Adenocarcinomas.

Journal of thoracic imaging
PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of epidermal growth factor receptor ( EGFR ) and TP53 mutations and to assess the models' capacities t...