AIMC Topic: Sensitivity and Specificity
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Artificial Intelligence for Real-Time Prediction of the Histology of Colorectal Polyps by General Endoscopists.
Annals of internal medicine
May 21, 2024
BACKGROUND: Real-time prediction of histologic features of small colorectal polyps may prevent resection and/or pathologic evaluation and therefore decrease colonoscopy costs. Previous studies showed that computer-aided diagnosis (CADx) was highly ac...
Sensitivity and Specificity of Using GPT-3.5 Turbo Models for Title and Abstract Screening in Systematic Reviews and Meta-analyses.
Annals of internal medicine
May 21, 2024
BACKGROUND: Systematic reviews are performed manually despite the exponential growth of scientific literature.
Enhanced multi-class pathology lesion detection in gastric neoplasms using deep learning-based approach and validation.
Scientific reports
May 21, 2024
This study developed a new convolutional neural network model to detect and classify gastric lesions as malignant, premalignant, and benign. We used 10,181 white-light endoscopy images from 2606 patients in an 8:1:1 ratio. Lesions were categorized as...
COVID‑19 detection from chest X-ray images using transfer learning.
Scientific reports
May 21, 2024
COVID-19 is a kind of coronavirus that appeared in China in the Province of Wuhan in December 2019. The most significant influence of this virus is its very highly contagious characteristic which may lead to death. The standard diagnosis of COVID-19 ...
Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.
European radiology experimental
May 20, 2024
BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).
Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction.
La Radiologia medica
May 18, 2024
PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases.
Performance of AI to exclude normal chest radiographs to reduce radiologists' workload.
European radiology
May 17, 2024
INTRODUCTION: This study investigates the performance of a commercially available artificial intelligence (AI) system to identify normal chest radiographs and its potential to reduce radiologist workload.
Deep learning for temporomandibular joint arthropathies: A systematic review and meta-analysis.
Journal of oral rehabilitation
May 17, 2024
BACKGROUND AND OBJECTIVE: The accurate diagnosis of temporomandibular disorders continues to be a challenge, despite the existence of internationally agreed-upon diagnostic criteria. The purpose of this study is to review applications of deep learnin...
A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.
La Radiologia medica
May 17, 2024
OBJECTIVE: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal g...
Artificial Intelligence in Anterior Chamber Evaluation: A Systematic Review and Meta-Analysis.
Journal of glaucoma
May 16, 2024
PRCIS: In this meta-analysis of 6 studies and 5269 patients, deep learning algorithms applied to AS-OCT demonstrated excellent diagnostic performance for closed angle compared with gonioscopy, with a pooled sensitivity and specificity of 94% and 93.6...
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