Abstract Purpose To review eXplainable Artificial Intelligence/(XAI) methods available for
medical imaging/(MI). Method A scoping review was conducted following the Joanna Briggs …

Since the onset of the COVID-19 pandemic in 2019, there has been a concerted effort to
develop cost-effective, non-invasive, and rapid AI-based tools. These tools were intended to …

Insufficient annotated data and minor lung lesions pose big challenges for computed
tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To …

To improve the detection of COVID-19, this paper researches and proposes an effective
swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method …

Pneumonia is a disease that aggravates the air sacs in one or the two lungs. The air sacs
might load up with liquid or discharge (purulent material), causing hack with mucus or …

During pandemic periods, there is an intense flow of patients to hospitals. Depending on the
disease, many patients may require hospitalization. In some cases, these patients must be …

Recently, under the condition of reducing nucleic acid testing for COVID-19 in large
population, the computer-aided diagnosis with the chest computed tomography (CT) image …

The rapid growth of electronic health (eHealth) systems has led to serious security and
privacy challenges, highlighting the critical importance of protecting sensitive healthcare …

Federated learning holds great potential for enabling large-scale healthcare research and
collaboration across multiple centres while ensuring data privacy and security are not …

The fundus image is often used in clinical diagnosis due to ease and safety of acquisition,
but the quality may be affected by environment and onsite operations. As low-quality …