Psoriasis is one of those hard-to-diagnose skin disorders which can be difficult to diagnose in its early stages. The main challenge in diagnosing psoriasis is the similarity of its symptoms to those of other diseases, which can result in a misdiagnosis and a delay in treatment. Using new and modern technologies in health care, especially in the early diagnosis of diseases, can significantly resolve this field’s challenges. This chapter aims to introduce an intelligent diagnosis system based on the interaction between IoT, Machine Learning (ML), and blockchain, which can be used to diagnose psoriasis early. The proposed intelligent detection system can collect and transmit data remotely using the Internet of Things (IoT) capabilities. ML technology analyzes data to produce models based on which disease risks can be predicted and preventive measures recommended. These models can diagnose diseases early by using the available data and patterns. The proposed intelligent detection system stores all data in the blockchain structure using permission-based blockchain tools such as Hyperledger Fabric (HLF). Hence, all data is encrypted with these blockchains’ (BPB) robust encryption mechanism before entering the blockchain structure. Therefore, privacy issues will be fully addressed when IoT is used in healthcare. In this way, the combination of blockchain, artificial intelligence, and the IoT in healthcare provides facilities such as accurate data collection, diagnosis and prevention of diseases, improvement of treatment, and secure communication between patients and physicians.