The use of research to address health-related issues, including medical, nutrition, and environmental health, is the focus of the multidisciplinary subject of the health science. It entails integrating multidisciplinary scientific research including machine learning techniques and AI technologies. A branch of this exploratory is the Network Medicine which aims at creating a new approach to biomedical science, combining principles and approaches from systems biology and network science to both understand the causes of human diseases, and find and develop new personalized treatments. Along this line, this exploratory also addresses the problem of building BioMedical knowledge graphs, which are at the cornerstone of advanced BigData analytical tools for BioMedical data, by designing and implementing an entity linker and a network synthesizer specialized on the language used in bio-medical research papers, more precisely, PubMed Central. Another point of view is the study of the way personal activities affect the health and performances of the people. The proliferation of new sensing technologies that provide reliable data streams extracted from every day personal activities or sport professionals. Combining this flow of (big) data with powerful data science and AI tools, we have the chance to unveil the great complexity underlying activity performances towards many challenging goals.