The first great data analysts who revolutionized the inference of relationships between variables were biostatisticians, not engineers or traditional statisticians. Pioneers like Fisher relied on ad hoc methods specifically designed to solve real-world biological problems. Advances in mathematical statistics and empirical processes were driven by the need to develop reliable methods for biostatistics, such as survival models and adaptive experimental designs. Biostatistics has always exceeded expectations in the search for efficient solutions to real-world problems, distinguishing itself from other fields. Today, artificial intelligence (AI) is on the rise and is often seen as the future of many fields of knowledge. However, I firmly believe that the true revolution in healthcare will not be driven only by AI system. By focusing on biological problems and models with a biologically interpretable basis, biostatistics must guide the future of digital medicine. However, as a dynamic ...