Machine Learning for IoT HealthCare Applications: A Review

Internet of Things and Machine Learning (ML) have wide applicability in many aspects of life, health care is one of them. With the rapid development and improvement of the internet, the conventional strategies for patient services diminished and supplanted with electronic healthcare systems. The use of IoT technology offers medical professionals and patients the most modern medical device environment. IoT things and Machine-Learning are valuable in various classifications from far off observing of the modern climate to mechanical mechanization. Moreover, medical care applications are principally indicating interest in IoT things in view of cost decrease, easy to understand and improve the personal satisfaction of patients. The latest applications for IoT medical treatment, investigated and still facing problems in the clinical environment, are needed for intellectual, creativity-based answers. In specific, portable, and implantable IoT model devices, investigated for calculating the data transmission. Implantable technologies lead to the natural substitution of the injured part of the human body. The creation of a wearable and implantable healthcare body area network faced several challenges that are illustrated in this study. In this paper, an overview of IoT and Machine Learning based on healthcare care demonstrated in detail, the applications that use in health care by incorporating Machine Learning (ML) for the Internet of Things (IoT) listed with all issues and challenges while using this application or devices for health care and their important usage. Also, algorithms used by Machine Learning in IoT for developing devices are indicated by showing previous work and classified each of them according to the used method.