Simple Summary Transfer learning plays a major role in medical image analyses; however,
obtaining adequate training image datasets for machine learning algorithms can be …

Mobile health (mHealth) apps show potential contributions as interactive systems for
managing users' health conditions. They are also used to improve health habits using …

Intelligent agents are showing increasing promise for clinical decision-making in a variety of
healthcare settings. While a substantial body of work has contributed to the best strategies to …

In this paper, we developed BreastScreening-AI within two scenarios for the classification of
multimodal beast images:(1) Clinician-Only; and (2) Clinician-AI. The novelty relies on the …

Artificial intelligence has the potential to transform many application domains fundamentally.
One notable example is clinical radiology. A growing number of decision-making support …

In this research, we take an HCI perspective on the opportunities provided by AI techniques
in medical imaging, focusing on workflow efficiency and quality, preventing errors and …

Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-
resolution tumor images to search for pathology patterns of interest. However, existing AI …

Background Patients with retinal diseases may exhibit serious complications that cause
severe visual impairment owing to a lack of awareness of retinal diseases and limited …

Blockchain (BC) and artificial intelligence (AI) technologies have independent applications
in multiple industries, including banking, finance, healthcare, construction, transportation …

As new forms of data capture emerge to power new AI applications, questions abound about
the ethical implications of these data collection practices. In this paper, we present clinicians' …