… deal with artefacts produced on clinical images requires further enquiry. Lastly the education
required for radiologists before tools can be used in clinical practice should be assessed as …

… artificial intelligence (AI), it is necessary to define the term. We can begin by defining what
we mean by intelligence. … , examines the challenges facing its implementation in the clinical …

… Within this context, AI techniques can play pivotal roles for image-based diagnosis and …
advances of artificial intelligence methods – particularly supervised machine learning and deep …

… US imaging from both clinical and basic perspectives. We also discuss US image preprocessing,
… the fundamental machine learning algorithms for US imaging, along with other medical …

… Artificial intelligence is a hot topic in medical imaging. The development of deep learning …
imaging. Prospective validation of AI tools will be required before reaching routine clinical …

… imaging has placed increasing demands on radiologists. In this scenario, artificial intelligence
(AI) … clinic. In this review, we discuss interpretative and non-interpretative uses of AI in the …

… Results: A total of 5069 images of oral mucosa lesions were used. The oral … an artificial
intelligence model for the automated classification of elementary lesions from oral clinical images, …

… MRI images for various clinical indications and pathologies were analyzed with the aid of
commercially available software for the automated DL-based and manual contouring of …

… deep learning and the promise of artificial intelligence (AI) in … use AI products in real-world
clinical situations. Adoption of … and the Checklist for Artificial Intelligence in Medical Imaging is …

… development of imaging biomarkers that have a significant impact on important clinical issues…
as a new technological clinical application of artificial intelligence and has shown results in …