The detection capability identifies AI-generated images and AI-edited real images, by capturing generation artifacts and semantic inconsistencies invisible to the human eye. Designed for ...

Researchers have developed a new artificial intelligence-based approach for detecting fatty deposits inside coronary arteries ...

Background and objectives Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.

The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges ...

Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...

Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models.

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in real scenarios.

Researchers improved a deep learning model that detects live bacteria in food samples within three hours. By training it to ...

Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...