The rapid advancements in Artificial Intelligence (AI) are reshaping various industries, and medicine is no exception. This track aims to explore the dynamic intersection between AI and medicine, examining how AI technologies are revolutionizing healthcare delivery, diagnosis, treatment, and patient care. The track will bring together researchers, practitioners, and industry experts to discuss cutting-edge developments, challenges, and future directions in this rapidly evolving field.
Objectives:

• To explore the current state of AI applications in medicine, including diagnostics, treatment planning, and patient management.
• To discuss the ethical, legal, and social implications of integrating AI into healthcare systems.
• To showcase innovative AI-driven solutions that enhance clinical decision-making and patient outcomes.
• To identify challenges and opportunities in the adoption of AI technologies in clinical practice.
• To foster interdisciplinary collaboration between AI researchers, healthcare professionals, and policymakers.

Key Topics:

• AI in Diagnostics: The use of machine learning algorithms in imaging, pathology, and genetic testing for more accurate and timely diagnoses.
• AI in Treatment and Management: Personalized medicine through AI-driven treatment plans, including drug discovery and precision therapy.
• AI in Patient Monitoring and Care: Applications of AI in wearable devices, remote monitoring, and telemedicine for continuous patient care.
• Ethics and AI in Medicine: Addressing the ethical challenges, including bias in AI algorithms, patient privacy, and informed consent.
• AI in Healthcare Operations: Improving healthcare efficiency through AI in hospital management, resource allocation, and workflow optimization.
• Future Trends in AI and Medicine: Emerging technologies such as AI-powered robotics, natural language processing in clinical settings, and AI in mental health.

Expected Outcomes:
A comprehensive understanding of the role of AI in transforming medical practice, healthcare delivery and hospital management systems.
Identification of key areas where AI can address unmet medical needs and improve patient outcomes.
Insights into the ethical considerations and regulatory frameworks necessary for responsible AI integration in medicine.
Networking opportunities for participants to collaborate on future research and projects in AI and healthcare.

Target Audience:
This track is designed for AI researchers, medical professionals, healthcare administrators, policymakers, and industry stakeholders interested in the application of AI in medicine. It will also benefit anyone interested in the future of healthcare and the role of emerging technologies in shaping it.

Guendalina Capece, Universitas Mercatorum, Italy
Tindaro Cicero, Universitas Mercatorum, Italy
Flavia Di Costa, Universitas Mercatorum, Italy
Daniela D’Auria, Universitas Mercatorum, Italy