Читать книгу The Internet of Medical Things (IoMT) - Группа авторов - Страница 63

Personal data is one of the main issues when dealing with data storage in cloud security. Classification of data in the cloud is the identification of a set of standards. This proposal depends on the type of security level content and access. We are able to provide a level of security in the cloud storage needed for privacy and restrictions on access to a set of data. We classified them based on analysis of multiple data elements and criteria. This paper focuses on data security for cloud technology environment. The main objective of this study was to classify data protection elements based on data. This data in sensitive and non-sensitive partitions winning better technology will improve. Sensitive data is sent to the cloud and sent via the data algorithm blowfish, while non-transmitting sensitive data are stored in the cloud server. Also, the clouds split isolated a separate partition and stored in data partition. But all data will be stored in the same cloud.

A clinical decision support system (CDSS) is an application that analyzes data to help healthcare providers make decisions, and improve patient care. A CDSS focuses on using knowledge management to get clinical advice based on multiple factors of patient-related data. Clinical decision support systems enable integrated workflows, provide assistance at the time of care, and offer care plan recommendations. Physicians use a CDSS to diagnose and improve care by eliminating unnecessary testing, enhancing patient safety, and avoiding potentially dangerous and costly complications. The applications of big data in healthcare include, cost reduction in medical treatments, eliminate the risk factors associated with diseases, prediction of diseases, improves preventive care, analyzing drug efficiency. Some challenging tasks for the healthcare industry are:

1 (i) How to decide the most effective treatment for a particular disease?

2 (ii) How certain policies impact the outlay and behavior?

3 (iii) How does the healthcare cost likely to rise for different aspects of the future?

4 (iv) How the claimed fraudulently can be identified?

5 (v) Does the healthcare outlay vary geographically?

These challenges can be overcome by utilizing big data analytical tools and techniques. There are four major pillars of quality healthcare. Such as real-time patient monitoring, patient-centric care, improving the treatment methods, and predictive analytics of diseases. All these four pillars of quality healthcare can be potently managed by using descriptive, predictive, and prescriptive big data analytical techniques.