Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …

The advancement of precision medicine in medical care has led behind the conventional
symptom-driven treatment process by allowing early risk prediction of disease through …

Purpose To demonstrate the value of pretraining with millions of radiologic images
compared with ImageNet photographic images on downstream medical applications when …

Radiomics refers to the extraction of mineable data from medical imaging and has been
applied within oncology to improve diagnosis, prognostication, and clinical decision support …

Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …

Data-driven machine learning (ML) has emerged as a promising approach for building
accurate and robust statistical models from medical data, which is collected in huge volumes …

Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …

Precision medicine is one of the recent and powerful developments in medical care, which
has the potential to improve the traditional symptom-driven practice of medicine, allowing …

Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …

Supervised training of deep learning models requires large labeled datasets. There is a
growing interest in obtaining such datasets for medical image analysis applications …