 This study presents a systematic review of studies that have used deep learning, DL, based on mobile health, mHealth, data for the diagnosis, prognosis, management, and treatment of major chronic diseases such as cardiovascular disease, diabetes, and cancer. The results show that DL algorithms using data captured from mobile devices can achieve satisfactory performance in diagnosing patients' conditions, predicting blood glucose levels, and detecting cancer. However, most studies did not provide details on the explainability of DL outcomes. Perspective studies are needed to demonstrate the value of applied DL in real-life mHealth tools and interventions. This article was authored by Andreas Triantofilidis, Hari Demos Kondilakis, Demetrius Kodahakis, and others.