week 3

Last but not least, this week we’ll dive into key concepts like reproducibility and external validation in AI research, and explore the crucial role of trust and explainability in clinical decisions. During this week, we also tackle the legal challenges of applying AI in healthcare. Finally, we explore the human element of AI-augmented healthcare and take a sneak peek into the future, focusing on AI’s role in precision and personalized medicine.

Intended Learning Outcomes

Here are some things you’ll be able to appreciate by the end of the week:

  • Understand Reproducibility and Trust in AI Models: Recognize the importance of dataset standardization, data representation, and external validation. Explore how the "black box" nature of deep learning models might affect trust in AI-driven decision-making.
  • Recognize Ethical, Legal, and Practical Implications of AI in Healthcare: Identify key legal and ethical challenges in AI-driven medicine, and understand the regulatory solutions proposed in Italy, the EU, and the US. Examine barriers to data sharing in hospitals and explore liability and accountability in cases of technological failures.
  • Examine the Relations Among AI, the Human Element, and Personalized Medicine: Understand how augmented intelligence enhances human expertise in healthcare and how healthcare institutions can collaborate with big tech to protect patient data. Discuss AI's crucial role in advancing personalized and precision medicine, and explore how digital twins could revolutionize medical research and clinical trials by predicting better treatment responses.