Endocrine Abstracts

Artificial intelligence (A.I.) impacts patient care but it is also evolving our educational system. Several experts have pointed out the benefits and limitations associated with its use in medicine, however the applications of A.I. in an educational context requires further discussion. The rising popularity of A.I. for medical solutions is evident from the increasing amount of research conducted on this subject, and Endocrine Education should not be an exception. Researchers have proposed that A.I. could be used to analyze data to identify struggling students, similarly it can be used to assist teachers in creating personalized methods for said students increasing the chances of success. On the other hand, future endocrinologists should be able to utilize the expansive databases and other appropriate tools, resulting in a massive volume of information that can overwhelm students. In this context mentorship on data management should be provided by main endocrine societies. Furthermore, electronic health records highlight the impact of natural language processing and affect medical education. Endocrinologists in the future could learn about the natural history of chronic diseases and better identify endocrine pathologies, greatly reducing the diagnosis timeframe. There is also an opportunity to develop Endocrine Healthcare Leaders with expertise in Big Data and A.I., this newly trained professional could be the bridge between clinicians and data specialists to develop A.I. Projects. Therefore, A.I. and its applications should be taught within Endocrine Societies and needs to be formalized to train the next generations of endocrinologists with a new set of skills that will directly impact not only our education system but patient care as well.