A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: coherent taxonomy, open issues and recommendation pathway solution

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, in order to identify the research landscape from the literature into a cohesive taxonomy. An extensive search was conducted for articles dealing with 'skin cancer', 'apps' and 'smartphone' or 'mHealth' in different variations to find all the relevant articles in three main databases, namely, Web of Science, Science Direct, and IEEE explore. These databases are considered wide enough to cover medical and technical literature. The final classification scheme outcome of the dataset contained 110 articles that were classified into four classes: development and design; analytical; evaluative and comparative; and review and survey studies. Afterwards, another filtering process was achieved based on the evaluation criteria error rate within the dataset, time complicity and reliability, which are used in skin cancer applications. The final classification scheme outcome of the dataset contained 89 articles distributed in mapping and crossover with four sections concluded from 110 articles. Development and design studies, analytical studies, evaluative and comparative studies and articles of reviews and surveys comprised of 48.3146%, 22.4719%, 16.8539% (15), and 12.3595% (11) of the reviewed articles, respectively. The basic features of this evolving approach were identified in these aspects. We also determined open issues in terms of evaluation and benchmarking that hamper the utility of this technology. Furthermore, with the exception of the 89 papers reviewed, the new recommendation pathway solution was described in order to improve the measurement process for smartphone-based skin cancer diagnosis applications.