A research team has developed a new method using artificial intelligence (a large language model) to measure unmet medical needs across all human diseases. The method defined 11 scoring criteria divided into three categories, which allow objective comparison of which diseases have the greatest need for new treatments. The researchers tested all 22,701 human diseases from the MONDO database and scored them all according to the established system. Agreement between experts was strong, with 95% of ratings differing by no more than one point, confirming the reliability of the method. The results showed a strong correlation with clinical data such as mortality rates and life years lost. The entire process took approximately one hour with a computational cost of $120 without missing data. This scalable methodology allows researchers, universities and healthcare organizations to adjust their research priorities according to unmet medical needs and make more efficient funding decisions for new treatments.