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During the past decades, in the era of wireless communications and embedded system, the concept of the Internet of Things (IoT) was first presented by Kevin Ashton in the year 1999 [1]. Along with the tremendous growth in the number of sensing devices connected to the Internet, we were a witness of emerging IoT into healthcare, transportation system, smart cities, agriculture, and other enterprises. The IoT benefits cooperation of diverse computing systems such as sensors and smart devices to cloud computers. On the other side, the internet and mobile communication facilitate the spatiotemporal connection between distant people with common experience and values. More recently, technological evolution is introduced by intelligent sensor devices installed in the physical and virtual realm of IoT to act as or on behalf of human beings: the virtual robots [2]. This creates the possibility for physical objects present in a self-organized manner without a central administration and leads to meaningful human-machine interaction in IoT scenario [3].

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Advanced technologies such as internet of things (IoT) and clouds have significantly influenced on modern medical monitoring systems. Analytical statistics derived from massive patients' medical data via different data analysis methods, contribute in remote medical monitoring, early diagnosis of diseases, predicting clinical events, and recommending vital health/medical instructions. According to existence of the same health/medical services in functional aspect, finding appropriate composite health/medical services by the patients has been remained as a major concern in modern medical systems. Regarding this challenge, in this paper, a medical monitoring scheme for cloud‐based IoT platform is proposed, in which the patients' medical conditions are derived through predicting diseases by mining her physiological data collected from IoT devices and other medical records. A disease diagnosis model is used to analyze the patients' medical data for the aim of offering a composite health/medical prescription. After confirming the outcomes by medical team, it is sent to the patient. Then, the patient indicates her nonfunctional requirements such as location, cost and time to find the most appropriate composite health/medical service based on her preferences. Experimental results reveal that the proposed scheme is successful in achieving effective diseases diagnosis for offering composite health/medical prescriptions.