The article presents a new way to make deep learning systems in medicine easier to understand. By creating a clear decision structure for medical diagnoses, the researchers can map out how a computer makes decisions like a doctor would. They developed a method to interpret these complex systems by communicating with them in a smart way. This method focuses on gaining the most information with the fewest questions. The researchers showed that accuracy and interpretability can go hand in hand, without sacrificing one for the other. Through simulations, they demonstrated how this approach works in practice for different types of medical diagnoses.