AIMC Topic: Sensitivity and Specificity

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Standalone deep learning versus experts for diagnosis lung cancer on chest computed tomography: a systematic review.

European radiology
PURPOSE: To compare the diagnostic performance of standalone deep learning (DL) algorithms and human experts in lung cancer detection on chest computed tomography (CT) scans.

Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.

International journal of neural systems
Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment of epilepsy. Currently, prediction methods using Convolutional Neural Network (CNN) primarily focus ...

The innovation of AI-based software in oral diseases: clinical-histopathological correlation diagnostic accuracy primary study.

BMC oral health
BACKGROUND: Machine learning (ML) through artificial intelligence (AI) could provide clinicians and oral pathologists to advance diagnostic problems in the field of potentially malignant lesions, oral cancer, periodontal diseases, salivary gland dise...

Artificial intelligence enables precision diagnosis of cervical cytology grades and cervical cancer.

Nature communications
Cervical cancer is a significant global health issue, its prevalence and prognosis highlighting the importance of early screening for effective prevention. This research aimed to create and validate an artificial intelligence cervical cancer screenin...

Artificial Intelligence for Real-Time Prediction of the Histology of Colorectal Polyps by General Endoscopists.

Annals of internal medicine
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...

Enhanced multi-class pathology lesion detection in gastric neoplasms using deep learning-based approach and validation.

Scientific reports
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
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
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).