Journal of medical engineering & technology
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Big data analytics are gaining popularity in medical engineering and healthcare use cases. Stakeholders are finding big data analytics reduce medical costs and personalise medical services for each individual patient. Big data analytics can be used in large-scale genetics studies, public health, personalised and precision medicine, new drug development, etc. ⋯ Major methods, platforms and tools of big data analytics in medical engineering and healthcare are also presented. Advances and technology progress of big data analytics in healthcare are introduced, which includes artificial intelligence (AI) with big data, infrastructure and cloud computing, advanced computation and data processing, privacy and cybersecurity, health economic outcomes and technology management, and smart healthcare with sensing, wearable devices and Internet of things (IoT). Current challenges of dealing with big data and big data analytics in medical engineering and healthcare as well as future work are also presented.
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Since the start of the COVID-19 pandemic there has been much debate in the media on whether masks should be worn to stop the spread of the virus. There are two ways in which they could work. Firstly, to protect the person wearing the mask, and secondly, to reduce the likelihood of the person wearing the mask passing the disease on to anyone else. ⋯ The method used in this study was to measure the change in relative humidity when wearing a mask, compared to no mask, in various scenarios, based on the assumption that as the virus is air-borne the smaller the increase in humidity the less the spread of the virus. The results above show that the use of a mask, excluding some simple home-made ones, significantly reduces the spread of humidity. However, their effectiveness is device specific and needs to be considered in greater detail for each type of mask, especially the direction of escaping air when forward flow is blocked.