An analytical model for personalization of medical treatments using machine learning techniques

Abstract

The adoption of technology in the area of healthcare over the years has helped in better diagnosis and treatment of patients. Considering all the sectors that are benefitted from the advancements in technology, healthcare seems to be one of the most important ones. The dramatic improvements that have been made in the areas of networking and computing have expanded options for treatments and have transformed the way that clinicians perform their jobs. newlineAs the technology started improving and costs came down, several practices, policies, and data standards were created for the encouraging hospitals and clinics to adopt new technology in terms of imaging machines, medical equipment, and everyday record keeping. Medical Records in paper form got replaced by its digitized form as EHR (Electronic Health Records). This made accessing of health data like test results or diagnoses easier, more efficient, and more secure. It has now become a standard practice to use electronic health record-based systems or such technologies and engage patients too while creating treatment plans. Nevertheless, a big challenge that such systems have to face is dealing with a huge amount of unstandardized, unintegrated data that has been accumulated. At present, many healthcare organizations have a wealth of data that they can put to use to improve their business processes and procedures, but they lack the kind of tools or expertise to uncover relevant patterns and insights in the data that they have. More advanced technologies in the area of Cloud Computing, Blockchain and Machine Learning, and Artificial Intelligence are capable of helping healthcare organizations uncover patterns in such huge amounts of unstructured data and also make that data more manageable and secure. newlineMost healthcare organizations have accumulated such a large amount of data that it has almost become impossible to analyze it without the help of Artificial Intelligence and Machine learning techniques.