Breast cancer is the most common cancer in women both in developed and developing countries. More than half of all cancer mobile application concern breast cancer. Gamification is widely used in mobile software applications created for health-related services. Current prevalence of gamification in breast cancer apps is unknown and detection must be manually performed. The purpose of this study is to describe and produce a tool allowing automatic detection of apps which contain gamification elements and thus empowering researchers to study gamification using large data samples.

In clinical practice, a misdiagnosis can lead to incorrect treatment, delayed treatment, or in some cases, no treatment at all; consequently, the condition of a patient may worsen to varying degrees, in some cases proving fatal. The accurate 3D reconstruction of organs, which is a pioneering tool of medical image computing (MIC) technology, plays a key role in computer aided diagnosis (CADx), whereby enabling medical professionals to perform enhanced analysis on a region of interest.

Sleep and physical activity are human behaviors that play a major role in our health. Poor sleep or lack of physical activity have been found to increase health risks and reduce quality of life. The rapid adoption and evolution of pervasive computing systems, both in the health and wellness domain, are creating a new data-intensive context in which we can learn about the sleep and physical activity patterns of individuals. In this paper we provide an overview of the toolkit we have developed to conduct research on personal health data about sleep and physical activity.

Cancer is one of the most prevalent diseases in Europe and the world. Significant correlations between dietary habits and cancer incidence and mortality have been confirmed by the literature. Physical activity habits are also directly implicated in the incidence of cancer. Lifestyle behaviour change may be benefited by using mobile technology to deliver health behaviour interventions. M-Health offers a promising cost-efficient approach to deliver en-masse interventions.