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A new computing paradigm that has been growing in computing systems is fog computing. In the healthcare industry, Internet of Things (IoT) driven fog computing is being developed to speed up the services for the general public and save billions of lives. This new computing platform, based on the fog computing paradigm, may reduce latency when transmitting and communicating signals with faraway servers, allowing medical services to be delivered more quickly in both spatial and temporal dimensions. One of the necessary qualities of computing systems that can enable the completion of healthcare operations is latency reduction. Fog computing can provide reduced latency when compared to cloud computing due to the use of only low-end computers, mobile phones, and personal devices in fog computing. In this paper, a new framework for healthcare monitoring for managing real-time notification based on fog computing has been proposed. The proposed system monitors the patient’s body temperature, heart rate, and blood pressure values obtained from the sensors that are embedded into a wearable device and notifies the doctors or caregivers in real time if there occur any contradictions in the normal threshold value using the machine learning algorithms. The notification can also be set for the patients to alert them about the periodical medications or diet to be maintained by the patients. The cloud layer stores the big data into the cloud for future references for the hospitals and the researchers.

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A retrospective record-based cohort design was conducted including all patients admitted with diagnosis of CVT in 2 main tertiary hospitals in Aseer Region between 2015 to the end of 2018. The study hospitals were Aseer Central Hospital and Armed Forces Original ArticleHospitals Southern Region. The data were collected by structured data sheets, including sociodemographic data. Assessment of known risk factors for CVT, clinical presentation, treatment received, and clinical outcome after treatment were extracted. Results:The study included 119 patients with CVT, whose ages ranged from 15 to 97 years, with a mean age of 35.5-+14.1 years. Majority of the patients were females )81.5%(. Headache was the most presenting )82.4%( symptom, followed by vomiting )30.3%( and a decreased level of consciousness. Thirty-three cases )27.7%( had complications, and recanalization was recorded among 92 cases )94.8%( based on follow up vascular imaging. Conclusion:The study revealed that most of the cases of CVT had favorable clinical outcome and recanalization, especially those who had a shorter duration untildiagnosis. Young females were the most affected group.

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adipogenic differentiation inducer, can affect the subcutaneous layer in human skin in vivo. Although we still do not know the exact roles of the aged subcutaneous layer, we believe that an understanding about this layer may provide us with new insights and strategies for skin antiageing.

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