Description
Book SynopsisThis book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs).
Table of ContentsMachine Learning for Drug Discovery and Manufacturing.- Knowledge Strategies Influencing on The Epidemiologists Performance of The Qeshm Island’s Health Centers.- Healthcare: In the Era of Blockchain.- Securing Healthcare records using Blockchain: Applications and Challenges.- Authentication Schemes For Healthcare Data Using Emerging Computing Technologies.- Biomedical data classification using fuzzy clustering.- Applications of Machine Learning in healthcare With a Case Study of Lung Cancer Detection Through Deep Learning Approach.- Fetal Health Status Prediction During Labor and Delivery Based on Cardiotocogram Data using Machine and Deep Learning.- Blockchain and AI: Disruptive Digital Technologies in Designing the Potential Growth of Healthcare Industries.- Recommendation Systems for Cancer Prognosis, Treatment and Wellness.- A Real Time Data Mining-Based Cancer Disease Classification Using KEGG Gene Dataset.- SOLUTION ARCHITECTING ON REMOTE MEDICAL MONITORING WITH AWS CLOA Domain Oriented Framework for Prediction of Diabetes Disease and Classification of Diet using Machine Learning TechniquesUD AND IOT.- An Accurate Swine Flu Prediction and Early Prediction Using Data Mining Technique
