AIMC Topic: Sensitivity and Specificity

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Edge Computing System for Automatic Detection of Chronic Respiratory Diseases Using Audio Analysis.

Journal of medical systems
Chronic respiratory diseases affect people worldwide, but conventional diagnostic methods may not be accessible in remote locations far from population centers. Sounds from the human respiratory system have displayed potential in autonomously detecti...

Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre clinical study.

Scientific reports
To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional endoanal ultrasound (EAUS). A prospective, comparative, multicentre, international study. Poland, Czec...

Diagnostic accuracy of artificial intelligence for dental and occlusal parameters using standardized clinical photographs.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: SmileMate (SmileMate, Dental Monitoring SAS, Paris, France) is an artificial intelligence (AI)-based Web site that uses intraoral photographs to assess patients' dental and orthodontic parameters and provide a report. This study aimed t...

Deep Learning-Based Diagnostic Model for Parkinson's Disease Using Handwritten Spiral and Wave Images.

Current medical science
OBJECTIVE: To develop and validate a deep neural network (DNN) model for diagnosing Parkinson's Disease (PD) using handwritten spiral and wave images, and to compare its performance with various machine learning (ML) and deep learning (DL) models.

Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...

Data-driven AI platform for dens evaginatus detection on orthodontic intraoral photographs.

BMC oral health
BACKGROUND: The aim of our study was to develop and evaluate a deep learning model (BiStageNet) for automatic detection of dens evaginatus (DE) premolars on orthodontic intraoral photographs. Additionally, based on the training results, we developed ...

AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.

European radiology
OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect clinically significant prostate cancer (PCa) using multiparametric magnetic resonance imaging (MRI) is lacking. We compared a new AI solution, valida...

Segmentation of the nasopalatine canal and detection of canal furcation status with artificial intelligence on cone-beam computed tomography images.

Oral radiology
OBJECTIVES: The nasopalatine canal (NPC) is an anatomical formation with varying morphology. NPC can be visualized using the cone-beam computed tomography (CBCT). Also, CBCT has been used in many studies on artificial intelligence (AI). The "You only...

Toward a rapid, sensitive, user-friendly, field-deployable artificial intelligence tool for enhancing African swine fever diagnosis and reporting.

American journal of veterinary research
OBJECTIVE: African swine fever (ASF) is a lethal and highly contagious transboundary animal disease with the potential for rapid international spread. Lateral flow assays (LFAs) are sometimes hard to read by the inexperienced user, mainly due to the ...