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Enabling Healthcare 4.0 for Pandemics


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1.1 above shows the confirmed cases in the top three countries in number of cases across the world, starting from March, 2020 till mid July 2020. The US has the highest number of cases, followed by Brazil and then India on number three in the number of confirmed COVID-19 cases [6].

Schematic illustration of diagnosis of COVID-19 using support vector based machine learning approach.

      Machine Learning may present a solution for detecting COVID Infection at an early stage. A proposed machine learning model has been defined here, which can diagnose if patient is having SARS Cov 2 contagion using the CT scan images of Chest and Lungs [5].

      1.2.1 Machine Learning to Identify the People who are at More Risk of COVID-19

      1.2.2 Machine Learning to Speed Up Drug Development

Schematic illustration of Machine learning process for drug development.

      1 First researchers gather the data collected from various resources about COVID-19, its associated symptoms, categories of patients, available secondary treatments given by the doctors etc.

      2 After data collection, learning from that collected data can be done and compared with the diseases with similar symptoms and severity to determine the medications given in similar set of diseases.

      3 After learning and observation, a blended mixture of chemicals can be prepared as a testing medicine to check whether this mixture is useful in the treatment or cure from the illness.

      4 This blended mixture is now tested to a limited set of people and this process is known as human trial to observe the effectiveness of the medicine in order to decide whether this drug is safe and successful for people fighting with Corona Virus.

      5 If the results seems successful, then another set of trials can be performed with large group of people, otherwise the researcher try to make some changes in the blended chemicals or its composition to see whether the medicine works or not again by conducting human trials.

      6 The last step of this process is to let the machine learn itself from the above experiences and the results obtained from the various trials and then decide that which set of blended chemicals can be used further in case the above process gets fail.

      1.2.3 Machine Learning for Re-Use of Existing Drugs in Treating COVID-19

Schematic illustration of machine learning approach for reuse of drug in COVID-19.