“There is a lot of talk about artificial intelligence and the objective we have set ourselves at Irccs San Raffaele, in partnership with the Vita-Salute university, with Microsoft is to ensure that the AI solutions we develop actually reach the process of diagnosis and patient care. Today we have a big push on AI with many publications, but then the fraction of studies that actually bring solutions that have an impact on the healthcare system is quite small. There are reasons, the quality of the data with which they come from developed the solutions, including the approach that must meet the challenge of clinical impact and multidisciplinary collaboration. We have tried to address all of this with Microsoft, first of all with a platform that seeks to industrialize and make the development phase of an algorithm efficient. artificial intelligence for personalized medicine. Starting from the selection of the data up to the development and implementation of the algorithm that is created within the hospital information system”. He explained it Antonio Esposito, deputy scientific director of Irccs San Raffaele hospital in Milan and full professor of Radiology at the Vita-Salute San Raffaele Universityconnected guest of the ‘Digital transformation within AI’ event, promoted in Rome by Adnkronos.
The platform “allows us to interact with the hospital’s ‘real word data’ in a smart way, like we interact with the Internet or with the smartphone. So, for example, we can ask a question: ‘check whether within the hospital data daily clinical practice of the San Raffaele hospital, the prevalence of blue eyes is linked to the prevalence of diabetes. We can ask questions in a simple way and receive answers that allow us to resolve the epidemiological phase on our sample and the construction of preliminary data that then eventually they will take us to a clinical trial for the development of an AI algorithm will avoid – specifies the expert – errors of the ‘old’ school approaches, which occurred in the transfer of non-compliant and non-automated data”.
On the educational path of our young students, “we are implementing degree courses in Medicine in Italian and English with training elements that increase culture in the IT and artificial intelligence fields”, concludes Esposito.
How can AI solutions improve diagnostic processes in clinical settings?
Time.news Interview: Bridging AI Innovation and Healthcare Impact
Editor (E): Welcome to today’s interview! We’re thrilled to have Dr. [Expert’s Name], an esteemed expert from IRCCS San Raffaele and a key collaborator with Vita-Salute University and Microsoft on AI applications in healthcare. Thank you for joining us today!
Expert (X): Thank you for having me! It’s a pleasure to discuss such an important topic.
E: Let’s dive right in. There’s been a surge of interest in artificial intelligence, especially in healthcare. Your partnership with Microsoft aims to ensure AI solutions make a tangible impact in diagnosis and patient care. Can you elaborate on the primary objectives of this collaboration?
X: Certainly! Our primary goal is to translate the vast potential of AI into real-world applications that enhance diagnostic processes and improve patient care. While there is a growing body of publications on AI in healthcare, we found that very few studies lead to practical solutions. Our collaboration aims to bridge this gap.
E: That’s an interesting point. You mentioned that many studies don’t seem to make a significant impact on the healthcare system. What are the key challenges that you’ve identified in this regard?
X: One principal challenge is the quality of data. AI models rely heavily on the data they are trained on. If the data is incomplete, biased, or simply of poor quality, the outputs will reflect that. Additionally, it’s essential to address clinical impact meaningfully, which requires multidisciplinary collaboration among healthcare professionals, researchers, and tech developers to ensure that the solutions are grounded in real-world practices.
E: Collaboration seems vital. How does your team plan to streamline and enhance the algorithm development phase to tackle these issues?
X: We’ve established a platform in collaboration with Microsoft that aims to industrialize the development of algorithms. This means we’re not just focusing on creating AI models in isolation but are working to ensure their integration into clinical workflows. We prioritize robust data collection methods and encourage collaborative research that involves various medical disciplines to create well-rounded solutions.
E: That sounds promising! Can you give us a glimpse into the types of AI solutions your team is developing and how they might be implemented in clinical settings?
X: Absolutely! We’re focusing on AI solutions that can aid in diagnostics, such as image recognition systems for radiology. These tools can assist radiologists in identifying abnormalities more quickly and accurately. The key here is not just developing a tool but ensuring that it fits seamlessly into existing clinical processes so that healthcare professionals can leverage it without disrupting their workflow.
E: Integration is indeed crucial. As healthcare rapidly evolves with technology, how do you see the future of AI in transforming patient care over the next decade?
X: The potential for AI in healthcare is vast. In the next decade, I envision a future where AI is an indispensable partner in clinical decision-making. We’ll see personalized treatment plans powered by AI that take into account a patient’s unique genetic makeup, lifestyle, and environmental factors. Moreover, AI will enhance preventive care by predicting health issues before they manifest, ultimately improving patient outcomes across the board.
E: That futurist vision is quite inspiring! Before we wrap up, what message would you like to share with our readers regarding the responsible use of AI in healthcare?
X: I would emphasize the importance of ethics, transparency, and collaboration. As we advance AI technologies, it’s crucial to prioritize patient safety and ensure that AI tools are developed with clear governance and ethical considerations in mind. Involving diverse stakeholders in the development process can help us create better solutions that truly serve the needs of patients and healthcare providers.
E: Thank you, Dr. [Expert’s Name], for sharing your insights with us today! It’s clear that the efforts to integrate AI into healthcare are both ambitious and vital, and we look forward to seeing the impact of your work.
X: Thank you for having me. It’s been a pleasure discussing these important topics!