My name is Adrian Mosquera. I'm from Spain, a hematology MD and PhD working at University Hospital of Santiago de Compostela in Spain. And I'm here today to discuss with you about generative AI and its role in medicine and particularly in hematology. So you've probably been hearing a lot of things about AI and how can it be applied in the field of medicine. And we have broadly two different approaches. The first one is discriminative AI. So in this field we just apply machine learning models that can help us guiding which patients are of high risk, which patients are more likely to respond to one therapy or the other. And this is very useful and can be obviously the matter of a lot of research approaches based on integration of molecular data, imaging data, clinical parameters, etc. However, there is a very rapidly growing field which is generative AI. So generative AI is not so focused on discriminating clusters of patients or of elements in a set, but it's more interested or more devoted to the development of whole probabilistic models. So what this means is that generative AI is capable of understanding complex relationships between elements in a set. And when these elements in a set are words, it can generate contextually correct language. And this is the foundation of tools like CHAT-GPT, DeepSeq, Mistral, etc. So in our research facility we are developing a new tool whose name is Code Red, in Spanish, Código Rojo. And it is intended to cover the whole medicine with very specific chatbots that are trained by doctors to solve particular doubts about each a different type of medical disorder. So we started in hematology because this is my domain of knowledge, but it has rapidly moved and nowadays we cover all different medical disciplines, pharmaceutical drugs and chemotherapy combinations, and even aesthetic medicine. So this tool is not only capable of connecting validated medical contexts with generative AI tools, it can also integrate voice, it can also integrate image processing, and obviously also can produce outputs in reference format that can be the basis for additional discussion with patients. So what we are seeing today is that doctors are very interested in these kind of tools because they facilitate their daily duties, particularly in fields where they are not very top experts. For example, I am a doctor in hematology and I know a lot about lymphoma and CLL, but I know very little about thyroid disorders or cardiac complications or pneumonia. So I use this kind of technology to enhance my capacities where I'm not capable of delivering an optimal care, and this has helped me a lot in my daily duties. So I think this is going to be really a change in paradigm for medical applications. So in my opinion, generative AI is going to transform the way we do medicine in our daily routine, in clinical practice, and I think Código Rojo, code red, is a tool that can hold a lot of promise for growing up and becoming a new standard in the field. So thank you for your attention and I hope you can enjoy it and try to find in the web our Código Rojo webpage and use it for your educational purposes. Thank you.
HealthTree • July 10, 2025