AIMC Topic: Sensitivity and Specificity

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Meta-analysis of AI-based pulmonary embolism detection: How reliable are deep learning models?

Computers in biology and medicine
RATIONALE AND OBJECTIVES: Deep learning (DL)-based methods show promise in detecting pulmonary embolism (PE) on CT pulmonary angiography (CTPA), potentially improving diagnostic accuracy and workflow efficiency. This meta-analysis aimed to (1) determ...

Automated Evaluation of D-Score for Facial Dysmorphism Analysis in Central African Children With Developmental Disorders.

Annals of human genetics
INTRODUCTION: Dysmorphism is an important characteristic, but its evaluation is largely subjective. A good clinical assessment (dysmorphism) can facilitate a more accurate and efficient diagnosis. We therefore evaluated an automated artificial intell...

Establishment of an intelligent analysis system for clinical image features of melanonychia based on deep learning image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Melanonychia, a condition that can be indicative of malignant melanoma, presents a significant challenge in early diagnosis due to the invasive nature and equipment dependency of traditional diagnostic methods such as nail biopsy and dermatoscope ima...

CBCT radiomics features combine machine learning to diagnose cystic lesions in the jaw.

Dento maxillo facial radiology
OBJECTIVE: The aim of this study was to develop a radiomics model based on cone beam CT (CBCT) to differentiate odontogenic cysts (OCs), odontogenic keratocysts (OKCs), and ameloblastomas (ABs).

Derivation and validation of an artificial intelligence-based plaque burden safety cut-off for long-term acute coronary syndrome from coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging
AIMS: Artificial intelligence (AI) has enabled accurate and fast plaque quantification from coronary computed tomography angiography (CCTA). However, AI detects any coronary plaque in up to 97% of patients. To avoid overdiagnosis, a plaque burden saf...

A Meta-Analysis of the Diagnostic Test Accuracy of Artificial Intelligence for Predicting Emergency Department Revisits.

Journal of medical systems
The revisit of the emergency department (ED) is a key indicator of emergency care quality. Various strategies have been proposed to reduce ED revisits, including the use of artificial intelligence (AI) models for prediction. However, AI model perform...