Soft Computing Technique for Block Chain Enabled Secure Healthcare System

Recent study shows that the integration of AI and Blockchain in the field of healthcare we can decrease many loopholes by integrating AI & Blockchain techniques. AI algorithms works better based on data input, which should be strong, deduce, and make final judgments. The machine learning algorithms work better when information is gathered from a data vault that is solid, secure, trusted, and tenable. On other hand Blockchain which is a scattered information system on which information are kept and transferred in a way that's cryptographically authenticated, certified, and acceptable by all mining nodes. The sensitive personal data of the patients are often securely stored within the Blockchain system which is stored with high reliable and tough, and can't be tampered with. When Smart Agreement are used for machine learning algorithms to form decisions and perform analytics, the result of those decisions are often trusted and undisputed. These blockchain secured dataset are used for the AI and ML algorithms. We use support vector machine algorithm as a Soft Computing Technique to demonstrate here. The main feature e of support vector machine algorithm is to find a hyper plane in an N-dimensional space (N - the number of features) that separates and categories the data points. Our objective is to find decision boundaries that classify maximum distance between data points of both the objects. We get better reinforcement by finding margins having more distance which also helps future data points that can be segregated with more confidence. The integration of AI and blockchain helps in creating strong and secure decentralized system for the real world application like healthcare system wherein AI-driven systems must collect, store, and utilize.