dsh-blood-pressure

In everyday conversations, whether a blood pressure reading falls into the normal, elevated, or hypertensive range is a question people ask constantly. Reaching for a webpage or an API call feels natural, but in offline setups, embedded dialog flows, or pure local model-inference pipelines, network access is simply not an option. That is exactly the gap dsh-blood-pressure fills: a fully local, Node-based blood pressure classifier that never touches the network.

Its scope is deliberately narrow and precise. It accepts standard blood pressure parameters such as systolic and diastolic values, applies the well-known classification thresholds, and returns a clear category label together with a concise suggestion. There is no ambiguity in the output, and a built-in reminder always advises users to follow the guidance of their physician for any medical decisions.

It is a good fit for developers building health-oriented chatbots, offline consultation systems, or local AI workflows that demand zero network dependency, low latency, and reproducible results. Licensed under MIT, this lightweight tool slots in as a practical blood-pressure reference component with minimal integration effort.