Machine learning approaches in COVID-19 diagnosis, mortality, and severity risk prediction: A review

The existence of widespread COVID-19 infections has prompted worldwide efforts to control and manage the virus, and hopefully curb it completely. One important line of research is the use of machine learning (ML) to understand and fight COVID-19. This is currently an active research field. Although there are already many surveys in the literature, there is a need to keep up with the rapidly growing number of publications on COVID-19-related applications of ML. This paper presents a review of recent reports on ML algorithms used in relation to COVID-19. We focus on the potential of ML for two main applications: diagnosis of COVID-19 and prediction of mortality risk and severity, using readily available clinical and laboratory data. Aspects related to algorithm types, training data sets, and feature selection are discussed. As we cover work published between January 2020 and January 2021, a few key points have come to light. The bulk of the machine learning algorithms used in these two applications are supervised learning algorithms. The established models are yet to be used in real-world implementations, and much of the associated research is experimental. The diagnostic and prognostic features discovered by ML models are consistent with results presented in the medical literature. A limitation of the existing applications is the use of imbalanced data sets that are prone to selection bias

Marketing Plan: Philips Mimo Baby Monitor

Parents will use any and all means to protect their infants, and would want the peace of mind of knowing that their baby is safe against dangers like SIDS, choking, crib dangers, and others. Supporting their mission “To improve people’s lives through meaningful innovation”, Philips has developed Mimo, a smart and accurate baby monitor that helps moms and dads get the reassurance they need to rest better. Mimo Smart Baby Monitor provides all the information parents want, whenever they want, and wherever they are in the world. The monitor is a machine washable outfit with respiration sensors that provides a constant stream of data about a baby’s sleep activity, breathing pattern, body position, skin temperature, and live audio, sent to an iPhone, iPad, or Android, and in realtime. The sensors do not actually touch the baby’s sensitive skin to make it safer. Mimo’s main targeted customers are first time parents who tend to be more concerned about infants health and needs, and busy parents who need to rest better at night in order to be more effective during the workday. Conjoint Analysis was used to figure out the customer needs; Mimo aims to meet those needs at a lower price point compared to the competitors. Philip’s direct and indirect channels of distribution that exists in different parts of the world will be leveraged on in the distribution of the product. In addition, multiple media outlets such as social media, television, and baby magazines, will be used to achieve the needed level of reach and awareness. We are forecasting to capture 30% of baby monitor’s market by the end of 2020