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Networks form the backbone of any healthcare system. Various databases were searched with relevant keywords, data were abstracted, and numerous papers were appraised for this synthesis. This compiled systematic review gives a comprehensive overview o...

Recent advances in the field of large language models (LLMs) underline their high potential for applications in a variety of sectors. Their use in healthcare, in particular, holds out promising prospects for improving medical practices. As we highlig...

Emerging infectious diseases (EIDs) pose an increasingly significant global burden, driven by urbanization, population explosion, global travel, changes in human behavior, and inadequate public health systems. The recent SARS-CoV-2 pandemic highlight...

In recent years, the advent of new experimental methodologies for studying the high complexity of the human genome and proteome has led to the generation of an increasing amount of digital information, hence bioinformatics, which harnesses computer s...

Deep learning has emerged as a powerful tool for medical image analysis and diagnosis, demonstrating high performance on tasks such as cancer detection. This literature review synthesizes current research on deep learning techniques applied to lung c...

Generative artificial intelligence (AI) is rapidly transforming healthcare systems since the advent of OpenAI in 2022. It encompasses a class of machine learning techniques designed to create new content and is classified into large language models (...

Ultrasound elastography (USE) or elastosonography is an ultrasound-based, non-invasive imaging method for assessing tissue elasticity. The different types of elastosonography are distinguished according to the mechanisms used for estimating tissue el...

Digital twins (DTs) are becoming increasingly popular in various industries, and their potential for healthcare in the metaverse continues to attract attention. The metaverse is a virtual world where individuals interact with digital replicas of them...

Chest X-ray (CXR) is one of the most common radiological examinations for both nonemergent and emergent clinical indications, but human error or lack of prioritization of patients can hinder timely interpretation. Deep learning (DL) algorithms have p...

Lung cancer is a leading cause of cancer-related deaths worldwide, emphasizing the significance of early detection. Computer-aided diagnostic systems have emerged as valuable tools for aiding radiologists in the analysis of medical images, particular...