Harvey: Welcome to the GPT podcast.com I'm Harvey, along with my co-host Brooks, and this is our AI in Healthcare Series. Today, we are discussing how generative AI can be useful in healthcare. It's an exciting topic with lots of potential. So, Brooks, what do you think about generative AI and its impact on healthcare?
Brooks: Hey, Dr. C, I've been really intrigued by the possibilities of generative AI in healthcare, it is going to allow us to more and more with less available healtcare workers. Can you give our listeners a brief overview of what generative AI is and how it can be applied in this industry?
Harvey: Absolutely, Brooks. Generative AI, a subset of deep learning, allows users to create content in multiple formats. In the context of healthcare, it has transformative use cases across the entire healthcare value chain. From personalized care and guided diagnosis to population health management, drug discovery, and operational efficiencies, generative AI has the potential to drive better patient outcomes and improve the overall efficiency of the healthcare system.
Brooks: That's fascinating, Harvey. Let's dive deeper into some of those applications. You mentioned personalized care and guided diagnosis. How exactly can generative AI assist in this area?
Harvey: Great question, Brooks! With the vast amount of data scattered across multiple sources, physicians often struggle to provide the most effective care to patients at the lowest cost. Generative AI can come to the rescue by tapping into patients' medical and family history, lifestyle, and other factors. It can summarize key data points and recommendations for follow-up, which physicians can review during patient visits. Imagine the ability to diagnose life-threatening diseases like sepsis or enhance medical imaging data for early disease detection. Generative AI acts as a co-pilot, freeing up resources and leading to better patient outcomes.
Brooks: That sounds incredibly powerful, Moving on to population health management, how can generative AI help payers and providers improve health outcomes for larger populations?
Harvey: Excellent question, Payers and providers need to gather data from multiple systems and sources, including socioeconomic factors, to develop policies that enhance the health outcomes of the entire population. Generative AI enables targeted campaigns and the identification of at-risk population sets, paving the way for more outreach. For instance, using large language models, personalized educational materials can be created for patients, providing them with information about their medical conditions and treatment options. Generative AI can even help overcome language barriers by translating medical information, ensuring effective outreach.
Brooks: Wow, that's incredibly insightful, Now, let's talk about drug discovery. How can generative AI assist in this complex process?
Harvey: That's a great question, Drug discovery is a lengthy and expensive process, but generative AI has the potential to revolutionize it. About one-third of the cost of drug development is spent on discovery, which can take years. Generative AI can help by generating novel drug candidates based on specific criteria and constraints provided by researchers. By analyzing large datasets on drug-target interactions and known drug properties, it can predict the efficacy and safety of new candidates. Generative AI also aids in identifying patient subgroups likely to respond to a particular drug, thus personalizing drug therapy and improving patient outcomes. According to Gartner, generative AI is expected to be used in 50% of drug discovery and development initiatives by 2025, potentially reducing costs and timelines.
Brooks: Putting on the Entrepreneur hat, it seems like time to market is the huge advantage here. 
Harvey: Yes and now combing this plus human genome to create personalize drugs! Currently a hemophiliac can be cured but the medication is 2.9 million dollars! What if AI now brings the cost down to the point that pharmaceutical companies now will work on rare diseases on treatments that they would not do because they could not profit from.
Brooks: That's truly groundbreaking, Lastly, let's discuss the operational efficiencies that generative AI can bring to healthcare. What are some examples of how it can streamline processes and improve productivity?
Harvey: Excellent question, A study by the National Bureau of Economic Research found that access to a generative AI-based conversational assistant increases workers' productivity by 14% on average. In healthcare, this translates into several benefits. By implementing generative AI, healthcare providers can reduce administrative burdens. For example, it can act as a physician scribe by automating the extraction of medically relevant information from discussions, summarizing the interaction, and integrating notes into electronic health record systems. This improves physician productivity and enhances the accuracy of patient data. Furthermore, generative AI enables more personalized and proactive communications through virtual agents, like chatbots, resulting in improved member experience and lower costs.
Harvey: And there you have it, folks! We've explored the various ways generative AI can revolutionize healthcare. From personalized care and guided diagnosis to population health management, drug discovery, and operational efficiencies, the potential is immense. Thank you, for your insightful questions and for joining me today on this AI in Healthcare journey.
Brooks: Thank you, for sharing your knowledge and guiding us through these exciting advancements in healthcare. I can't wait to see how generative AI continues to shape the future of the industry.
Harvey: Absolutely, And to all our listeners, stay tuned for more episodes of our AI in Healthcare Series. Until next time, this is  and  signing off from the GPT podcast.com