From Data to Diagnosis: Unleashing AI and 6G in Modern Medicine

Abstract

The convergence of artificial intelligence (AI) and sixth-generation (6G) wireless networks is poised to transform modern medicine from data acquisition to clinical diagnosis. This paper provides a comprehensive overview of the theoretical foundations and practical applications of AI and 6G in healthcare. We discuss how AI techniques, including machine learning and advanced data analytics, can harness the unprecedented speed, bandwidth, and ultralow latency of 6G networks to enable real-time medical data processing and decision support. Key enabling technologies such as the Internet of Things (IoT), edge computing, and big data analytics are examined in the context of an integrated AI+6G healthcare ecosystem. We explore generalized medical domains ranging from remote patient monitoring and telemedicine to intelligent medical imaging, robotic surgery, and smart hospitals. For each domain, we outline how AI algorithms convert raw data into diagnostic or predictive insights, and how 6G networking capabilities facilitate these processes with high reliability and security. Challenges regarding data privacy, security, interoperability, and the need for explainable AI in clinical settings are discussed alongside emerging solutions (e.g., federated learning and blockchain). Future research directions are identified to guide the responsible and effective deployment of AI-driven healthcare services over 6G networks. By fusing AI’s analytic power with 6G’s communication performance, the healthcare industry can move toward more proactive, personalized, and accessible patient care on a global scale.