METHODOLOGY: CT coronary angiography was performed on patients with Kawasaki disease diagnosed with coronary aneurysm or suspected to have coronary stenosis. Studies were performed using electrocardiogram-gated protocols. General anaesthesia was used in patients who were not cooperative for breathing control. Heart rate, image quality, and effective radiation dose were documented.
RESULTS: Fifty-two Kawasaki patients underwent CT coronary angiography to assess coronary artery lesions. Median heart rate was 88 beats per minute (range 50-165 beats/minute). Image quality was graded as excellent in 34 (65%) patients, good in 17 (32%), satisfactory in 1, and poor in 1 patient. Coronary artery aneurysm was found in 25 (bilateral = 6, unilateral = 19, multiple = 11). Thrombus was found in 11 patients resulting in partial and total occlusion in 8 and 3 patients, respectively. Coronary stenosis was noted in 2 patients. The effective radiation dose was 1.296 millisievert (median 0.81 millisievert). Better diagnostic imaging quality was significantly related to lower heart rate (p = 0.007).
CONCLUSION: Electrocardiogram-triggered CT coronary angiography provides a good diagnostic assessment of coronary artery lesions in children with Kawasaki disease.
Methodology: This article is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 and 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis was conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data.
Results: It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.