Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

Background Deep learning (DL), a subset of artificial intelligence (AI), has been applied to
pneumothorax diagnosis to aid physician diagnosis, but no meta-analysis has been …

Importance The efficient and accurate interpretation of radiologic images is paramount.
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …

Background Commercially available artificial intelligence (AI) tools can assist radiologists in
interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear …

Synergistic therapy strategy and prognostic monitoring of glioblastoma's immune response
to treatment are crucial to optimize patient care and advance clinical outcomes. However …

Background Chest radiography remains the most common radiologic examination, and
interpretation of its results can be difficult. Purpose To explore the potential benefit of …

Objective It is unknown whether artificial intelligence-based computer-aided detection (AI-
CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical …

In this study, the accuracy of the positional relationship of the contact between the inferior
alveolar canal and mandibular third molar was evaluated using deep learning. In contact …

This statement from the European Society of Thoracic imaging (ESTI) explains and
summarises the essentials for understanding and implementing Artificial intelligence (AI) in …

This paper presents LSHAD, an anomaly detection (AD) method based on Locality Sensitive
Hashing (LSH), capable of dealing with large-scale datasets. The resulting algorithm is …