Advancements in data acquisition and computational methods are generating a large
amount of heterogeneous biomedical data from diagnostic domains such as clinical …

Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with
considerable potential to improve early cancer detection and risk assessment, and to enable …

Glaucoma, a leading cause of irreversible blindness worldwide, poses significant diagnostic
challenges due to its reliance on subjective evaluation. Recent advances in computer vision …

Biobanking plays a pivotal role in biomedical research by providing standardized
processing, precise storing, and management of biological sample collections along with the …

Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly
being used in healthcare. Radiology and Radiography are on the frontline of AI …

Objectives Open-access cancer imaging datasets have become integral for evaluating novel
AI approaches in radiology. However, their use in quantitative analysis with radiomics …

Artificial intelligence (AI) is increasingly being used in the medical field, specifically for brain
cancer imaging. In this review, we explore how AI-powered medical imaging can impact the …

Glaucoma is the leading cause of irreversible blindness worldwide and poses significant
diagnostic challenges due to its reliance on subjective evaluation. However, recent …

Generative AI is rapidly transforming medical imaging and text analysis, offering immense
potential for enhanced diagnosis and personalized care. However, this transformative …

Determination of body composition (the relative distribution of fat, muscle, and bone) has
been used effectively to assess the risk of progression and overall clinical outcomes in …