Solution for identification, screening, and information of COVID-19, in populations when cities are quarantined.

It is a solution aimed at patients and health professionals.

It will be divided into 3 parts:

• Artificial Intelligence application for patient screening.
• Artificial Intelligence solution for healthcare professionals, to check scientific articles.
• Crossing the information obtained with the screening with the data from scientific articles through Big Data, and artificial intelligence.

The identification of COVID-19 can be faster through the Artificial Intelligence structure, using a mobile or web search in populations when cities are quarantined.

New and emerging Infectious Agents are a significant problem for global public health and technology can assist in the faster identification of possible cases to bring timely interventions. This is especially true for viral diseases that are easily and readily transmissible and have periods of asymptomatic infectivity.

The Coronavirus (SARSCoV2) described in December 2019 (COVID-19) has resulted in large quarantines worldwide to prevent further spread.

As of March 20, 2020, situational data from the World Health Organization indicate that there were about 209830 confirmed cases, including 8778 deaths from COVID-19, including cases in 168 countries. The Centers for Disease Control and Prevention and the World Health Organization have issued interim guidelines to protect the population and try to prevent the further spread of COVID-19 from infected individuals.

In order to reduce the identification time of a person under investigation for COVID-19 infection and the rapid isolation of that individual, we propose to collect the basic travel history, with the most common manifestations using a mobile phone or accessing online. These collected data can be used to assist in preliminary screening and early identification of possible individuals infected with COVID-19.

Thousands of data points can be collected and processed by artificial intelligence (AI) framework that can ultimately assess individuals who may be infected and classify them as risk, minimal risk, moderate risk and high risk of being infected by the virus. The identification of high-risk cases can be quarantined earlier, reducing the chance of spread.

The AI ​​algorithm identifies possible cases and sends alerts to the nearest health center, as well as the patient for an immediate health visit, if the interviewee is unable to go to the health center, the health department can send an alert to a unit mobile health, so you can make assessments. If a patient does not have an immediate risk of experiencing symptoms or signs related to viral infection, the AI-based health alert will be sent to the interviewee to notify them that there is no current risk of COVID-2019.

The recorded data of the algorithm using signs and symptoms will be collected before the groups that received alerts for possible identification and evaluation and for unidentified respondents. The proposed expanded analysis will help to understand whether there is any association with different sociodemographic variables and manifestations such as fever, signs and lower respiratory infections, including symptoms in individuals defined as with and without possible infection.

The applications of AI and deep learning have argued to be useful tools to aid diagnosis and decision-making about treatment. However, it is necessary to apply these techniques in a timely manner to obtain faster results. In addition to the cost-benefit ratio, the proposed modeling will be of great help in identifying and controlling when populations are closed due to the spread of the virus. In addition to these, our proposed algorithm can be easily extended to identify individuals who may have mild symptoms and signs.

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