The Iraqi healthcare services are struggling to regain their lost momentum. Many physicians and nurses left Iraq because of the current situation in the country. Despite plans of calling back the skilled health workforce, they are still worried by the disadvantages of their return. Hence, technology plays a central role in taking advantage of their profession through the use of telemedicine. Studying the factors that affect the implementation of telemedicine is necessary. Telemedicine covers network services, policy makers, and patient understanding. A framework that includes the influencing factors in adopting telemedicine in Iraq was developed in this study. A questionnaire was distributed among physicians in Baghdad Medical City to examine the hypothesis on each factor. The Statistical Package for the Social Sciences was utilized to verify the reliability of the questionnaire and Cronbach's alpha test shows that the factors have values more than 0.7, which are standard.
Diabetes mellitus is a serious health problem affecting the entire population all over the world for many decades. It is a group of metabolic disorder characterized by chronic disease which occurs due to high blood sugar, unhealthy foods, lack of physical activity and also hereditary. The sorts of diabetes mellitus are type1, type2 and gestational diabetes. The type1 appears during childhood and type2 diabetes develop at any age, mostly affects older than 40. The gestational diabetes occurs for pregnant women. According to the statistical report of WHO 79% of deaths occurred in people under the age of 60, due to diabetes. With a specific end goal to deal with the vast volume, speed, assortment, veracity and estimation of information a scalable environment is needed. Cloud computing is an interesting computing model suitable for accommodating huge volume of dynamic data. To overcome the data handling problems this work focused on Hadoop framework along with clustering technique. This work also predicts the occurrence of diabetes under various circumstances which is more useful for the human. This paper also compares the efficiency of two different clustering techniques suitable for the environment. The predicted result is used to diagnose which age group and gender are mostly affected by diabetes. Further some of the attributes such as hyper tension and work nature are also taken into consideration for analysis.
In the recent past, Internet of Things (IoT) plays a significant role in different applications such as health care, industrial sector, defense and research etc.… It provides effective framework in maintaining the security, privacy and reliability of the information in internet environment. Among various applications as mentioned health care place a major role, because security, privacy and reliability of the medical information is maintained in an effective way. Even though, IoT provides the effective protocols for maintaining the information, several intermediate attacks and intruders trying to access the health information which in turn reduce the privacy, security and reliability of the entire health care system in internet environment. As a result and to solve the issues, in this research Learning based Deep-Q-Networks has been introduced for reducing the malware attacks while managing the health information. This method examines the medical information in different layers according to the Q-learning concept which helps to minimize the intermediate attacks with less complexity. The efficiency of the system has been evaluated with the help of experimental results and discussions.