AIMC Topic: Sensitivity and Specificity

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Diagnostic accuracy of deep learning-based algorithms in laryngoscopy: a systematic review and meta-analysis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Laryngoscopy is routinely used for suspicious vocal cord lesions with limited performance. Accumulated studies have demonstrated the bright prospect of deep learning in processing medical imaging. In this study, we perform a systematic revie...

Clinical evaluation of accelerated diffusion-weighted imaging of rectal cancer using a denoising neural network.

European journal of radiology
BACKGROUND: To evaluate the effectiveness of a deep learning denoising approach to accelerate diffusion-weighted imaging (DWI) and thus improve diagnostic accuracy and image quality in restaging rectal MRI following total neoadjuvant therapy (TNT).

A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

Journal of clinical microbiology
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecu...

A Quantitative Comparison Between Human and Artificial Intelligence in the Detection of Focal Cortical Dysplasia.

Investigative radiology
OBJECTIVES: Artificial intelligence (AI) is thought to improve lesion detection. However, a lack of knowledge about human performance prevents a comparative evaluation of AI and an accurate assessment of its impact on clinical decision-making. The ob...

A machine-learning algorithm to grade heart murmurs and stage preclinical myxomatous mitral valve disease in dogs.

Journal of veterinary internal medicine
BACKGROUND: The presence and intensity of heart murmurs are sensitive indicators of several cardiac diseases in dogs, particularly myxomatous mitral valve disease (MMVD), but accurate interpretation requires substantial clinical expertise.

The Impact of Deep Learning on Determining the Necessity of Bronchoscopy in Pediatric Foreign Body Aspiration: Can Negative Bronchoscopy Rates Be Reduced?

Journal of pediatric surgery
INTRODUCTION: This study aimed to evaluate the role of deep learning methods in diagnosing foreign body aspiration (FBA) to reduce the frequency of negative bronchoscopy and minimize potential complications.

Artificial intelligence can be trained to predict -11 mutational status of canine mast cell tumors from hematoxylin and eosin-stained histological slides.

Veterinary pathology
Numerous prognostic factors are currently assessed histologically and immunohistochemically in canine mast cell tumors (MCTs) to evaluate clinical behavior. In addition, polymerase chain reaction (PCR) is often performed to detect internal tandem dup...

Machine learning-based discrimination of benign and malignant breast lesions on US: The contribution of shear-wave elastography.

European journal of radiology
PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode US and SWE images to differentiate benign from malignant solid breast lesions (BLs) and compare its performance with that of an expert radiologist.

A deep-learning system for diagnosing ectopic eruption.

Journal of dentistry
OBJECTIVES: To construct a diagnostic model for mixed dentition using a multistage deep-learning network to predict potential ectopic eruption in permanent teeth by integrating dentition segmentation into the process of automatic classification of de...