| Sumario: | Generative AI has the potential to transform every aspect of healthcare--from personalized patient care and drug discovery to enhanced medical imaging and robot-assisted surgeries. Physicians are taking advantage of state-of-the-art tools like ChatGPT to better connect with their patients and manage medical records. Like any emerging technology, there are benefits and challenges to using AI in medicine. Join us and leading industry experts to learn more about the next-generation AI tools, techniques, and applications driving innovation in healthcare. What you'll learn and how you can apply it Uncover the benchmarks and best practices enabling academic medical centers, pharmaceuticals, and health IT companies to build real-world LLM-based applications Discover how graph databases are reshaping life sciences, catalyzing breakthroughs, and steering healthcare toward impactful, personalized outcomes Explore powerful new generative AI tools designed to enhance the search capabilities of AI models and provide highly accurate LLMs for medical Q&A and summarization Learn how to develop LangChain applications for disease diagnosis and screening Discover generative, predictive, and hybrid AI models that offer comprehensive solutions for complex medical challenges This live course is for you because... You're an AI/ML engineer or data practitioner who wants to broaden your skill set and apply your knowledge to the healthcare industry. You're a medical practitioner looking to explore the latest advancements in AI technology. You're a healthcare leader who wants to implement AI technology in your organization. Recommended follow-up: Read Prompt Engineering for Generative AI (book) Read Developing Apps with GPT-4 and ChatGPT (book) Read Low-Code AI (book) Watch ChatGPT: Possibilities and Pitfalls (video) Read AI-First Healthcare (book) Read Generative Deep Learning, second edition (book) Please note that slides or supplemental materials are not available for download from this recording. Resources are only provided at the time of the live event.
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