Background As the use of smartphones continues to surge globally, mobile applications
(apps) have become a powerful tool for healthcare engagement. Prominent among these …

Mobile health skin cancer risk assessment campaign using artificial intelligence on a
population-wide scale: a retrospective cohort analysis GLO: 3NZ/01nov21: jdv17442-fig …

Background The integration of machine learning algorithms in decision support tools for
physicians is gaining popularity. These tools can tackle the disparities in healthcare access …

Background: Mobile health (mHealth) consumer applications (apps) have been integrated
with deep learning for skin cancer risk assessments. However, prospective validation of …

Smartphone applications (apps) are available to consumers for skin cancer prevention and
early detection. This study aims to review changes over time in the skin cancer apps …

Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have
been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is …

Background Machine learning algorithms achieve expert‐level accuracy in skin lesion
classification based on clinical images. However, it is not yet shown whether these …

Skin cancer is a growing public health problem. Early and accurate detection is important,
since prognosis and cost of treatment are highly dependent on cancer stage at detection …

Objective: This research aims to survey the efforts of researchers in response to the new and
disruptive technology of skin cancer apps, map the research landscape from the literature …

This research aims to review the attempts of researchers in response to the new and
disruptive technology of skin cancer applications in terms of evaluation and benchmarking …