Abstract: Agoraphobia has become a fairly frequent disorder in today's environment. Agoraphobia is a spectrum of mental diseases characterized by strong dread and anxious feelings. The majority of individuals are completely oblivious of the problem. It's critical to detect it early on so that doctors can provide better treatment and avoid it from becoming a major issue. Recently, machine learning algorithms have been employed to analyze patient records in order to spot anomalies by modeling human thought or forming logical inferences. In this study, we strive to detect agoraphobia in the early stages. The basic theories and uses of machine learning algorithms in identifying anxiety kinds are also reviewed in this project work. In our project work we build an application with model that can predict panic disorders at early stages using ML algorithm and finally our system will recommend the suitable solution plan for the patients. Our proposed work uses some supervised machine learning algorithms like Random Forest or KNN Algorithm or Decision Tree algorithm for prediction. Proposed system is a real time medical system useful for hospitals and doctors and built using Microsoft tools such as Visual Studio tool and SQL Server tool. We use these tools as they support more libraries, packages required to build real time applications

| DOI: 10.17148/IARJSET.2024.11806