We built a medical device that is in people's home that serves 2 purposes. First, it collects then sends data to the secure medical database that can be viewed after sufficient data has been collected and analyzed through an LSTM (long short-term memory) neural network to diagnose illness. Second, it can act as a communications or reminder portal. In order to collect data, we used a central Arduino that connects to the internet, with the esp8266 chip, and gathers data from modular auxiliary Arduinos, acting as sensors. The sensors we built can record glucose and oxygen levels in blood, weight, and pulse, but the sensors are not limited to just these, any and all sensors can be used as the device is modular. After the data is collected, it is sent with SSL encryption to a secure server. In order to determine if a person has a disease, we used machine learning. The neural network receives all of this as time series data and looks at whether there are trends in the measurements to predict whether a person has a disease. As no data exists yet, we created a fake disease to show the potential of our neural network and got an accuracy of 1. Aside from medical care, this project can apply to field health, water quality, climate change data, and many more fields. Early diagnosis of diseases can be extremely preventative and can help doctors employ the correct treatments before major symptoms occur which will cure numerous lives.