Artificial Intelligence (AI) and Machine Learning (ML) are now used in many research and industrial fields. Among these applications, they are widely employed to support medical professionals, patients, and caregivers in disease management, and they appear well-positioned to revolutionize the healthcare industry. Among the many applications of AI are medical imaging, predictive analytics, personalized treatment plans, and administrative automation. AI/ML can manage and integrate different data resources (clinical measurements and observations, biological data, experimental results, environmental information, and wearable device data) into models for managing human diseases. Incorporating AI/ML into medicine can enhance every stage of patient care, from risk stratification to diagnosis and therapy. Consequently, this chapter delves into how AI can positively affect every step of the diagnostic-therapeutic pathway, focusing on patient risk stratification, diagnosis, and disease treatment. Specifically, for each of these domains, we report the general approach of AI/ML in a real-world context. As shown, AI/ML-based approaches can improve healthcare workers’ knowledge, enable them to spend more time on direct patient care, and reduce fatigue.