Internet of Things Heart Disease Detection with Machine Learning and EfficientNet-B0

Heart disease is the main cause of mortality across all age groups in the modern world. Thus, the necessity for improving heart attack prediction utilizing various machine learning (ML) or deep learning (DL) approaches is necessary for the health industry. Globally, the prognosis of heart disease can be improved by early diagnosis and treatment. The IoT purpose is to make simple way of making energy, wealth, and saving time easy with smart environment. The machine learning (ML) or deep learning (DL) techniques are used in various Internet of Things (IoT)-based technologies to reduce time, money, energy, and others for better performance or development. In this paper, we are going to see different kinds of machine learning and deep learning used in Internet of Things for heart disease detection system. As a starting point, we provide an overview of machine learning before moving on to explore various learning methods including deep learning models. We used EfficientNet-B0, a new convolutional network with faster training speed and better parameter efficiency than previous models. EfficientNet-B0 shows promising results for heart disease prediction.