AIMC Topic: Sensitivity and Specificity

Clear Filters Showing 21 to 30 of 3084 articles

Radiomics-based MRI models for predicting breast cancer axillary lymph node involvement in comparison with Node-RADS: a proof-of-concept study.

European radiology experimental
BACKGROUND: Detection of axillary lymph node (LN) involvement is essential for staging breast cancer and optimizing treatment. This proof-of-concept two-center study explored the feasibility of magnetic resonance imaging (MRI) radiomics-based machine...

Diagnostic accuracy of artificial intelligence compared to family physicians and dermatologists for skin conditions: a systematic review and meta-analysis.

BMC primary care
CONTEXT: Artificial intelligence (AI) technologies are increasingly used for image recognition, especially for skin lesions. Due to what may be long wait times for dermatology appointments, general practitioners (GPs) are the gatekeepers when it come...

A noninvasive machine learning model using a complete blood count for screening of primary vitreoretinal lymphoma.

Nature communications
Primary vitreoretinal lymphoma (PVRL) is a rare and aggressive intraocular malignancy that is frequently misdiagnosed because of its nonspecific early manifestations and the lack of effective screening tools. We conduct a multicentre case-control stu...

Experimental approach for optimizing dose regimen of 68Ga-DOTATATE PET/CT for neuroendocrine tumor (NET) imaging in current high sensitivity scanners: Phantom and Patient Study.

Nuklearmedizin. Nuclear medicine
This study aimed to determine the optimized scan time and injected activity regimen for clinical Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.A NEMA PET body phantom was...

AUPA: weakly supervised approach for streamlining breast cancer diagnostic workflow by WSI histological type classification for efficient IHC triage.

Scientific reports
In routine breast cancer diagnostics, pathologists often review each case twice-first to determine the need for immunohistochemical (IHC) stains, and a second time to issue the final diagnosis-creating significant workload and delays. We present an a...

Cell-free DNA methylation and fragmentomics-based liquid biopsy for accurate esophageal cancer detection.

BMC cancer
BACKGROUND: Cell-free DNA is a promising source of biomarkers for early cancer detection and carries tumor-driven methylation and fragmentation features that have achieved good diagnostic efficacy across various cancers. However, there were no studie...

CarbaDetector: a machine learning model for detecting carbapenemase-producing Enterobacterales from disk diffusion tests.

Nature communications
Carbapenemase-producing Enterobacterales (CPE) are considered among the highest threats to global health by WHO. Their detection is difficult and time-consuming. We developed a random-forest machine learning (ML) model, CarbaDetector, to predict carb...

Performance of artificial intelligence-assisted ultrasound elastography in classifying benign and malignant breast tumors: a systematic review and meta-analysis.

BMC medical imaging
BACKGROUND: Precise benign and malignant breast tumors classification is essential for effective treatment planning and outcome prognostication. Medical imaging's capability to classify breast tumors has been greatly improved by the accelerated advan...

Describing the Performance and the Infrastructure Requirements of the Existing Artificial Intelligence (AI)-Based Diabetic Retinopathy (DR) Screening Algorithms for Diabetic Patients: an Umbrella Review.

Journal of medical systems
AI-based diabetic retinopathy (DR) screening algorithms have been evaluated in many countries and have shown promise in expanding access to screening, especially in low- and middle-income countries (LMICs). However, the literature lacks guidance on w...

A Single-step Platinum Nanoparticle-Enhanced Lateral Flow Immunoassay Platform for Rapid Detection of Influenza A Virus.

ACS infectious diseases
Lateral flow immunoassays (LFIAs) are widely used point-of-care (POC) diagnostic tools, but their limited sensitivity can hinder reliable diagnoses. To address this limitation, we developed a novel POC diagnostic platform for the highly sensitive det...