The identification of medical images is an essential task in computer-aided diagnosis,
medical image retrieval and mining. Medical image data mainly include electronic health …

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to
systematically review studies employing DL for periodontal and implantological purposes. A …

While deep learning models have become the predominant method for medical image
segmentation, they are typically not capable of generalizing to unseen segmentation tasks …

Medical data are present in large amount and this is difficult to process for the diagnosis and
Healthcare organization requires effective technique to handle big data. Existing techniques …

Human Skin cancer is commonly detected visually through clinical screening followed by a
dermoscopic examination. However, automated skin lesion classification remains …

Deep learning has revolutionized the detection of diseases and is hel** the healthcare
sector break barriers in terms of accuracy and robustness to achieve efficient and robust …

Considering the efficiency and security of healthcare data processing, indiscriminate data
collection, annotation, and transmission are unwise. In this article, we propose the …

Abstract Model-agnostic meta-learning (MAML) is one of the most successful meta-learning
algorithms. It has a bi-level optimization structure where the outer-loop process learns a …

Foundation models, often pre-trained with large-scale data, have achieved paramount
success in jump-starting various vision and language applications. Recent advances further …

The diagnosis of oral squamous cell carcinoma or oral leukoplakia and the presence or
absence of oral epithelial dysplasia is carried by pathologists. In recent years, deep learning …