Abstract: Disclosed herein are methods and systems for implementing a machine learning architecture for detecting early adopters. A method includes receiving clinical data; training, using a supervised or unsupervised learning technique, a machine learning model (e.g., a neural network, a support vector machine, or a random forest) to generate a score identifying a likelihood to prescribe a medical product; generating, by the machine learning model, a score indicating a likelihood of a first medical personnel to prescribe a type of medical product within a defined time period; and causing a display at a client device based on the score.