Elias on Windows Pc

ELIAS (Laboratory Epidemiology with Artificial Intelligence in Health) is an application developed based on research developed by UFRN to help combat COVID-19. With it, it is possible to monitor the population's diseases in a massive and automatic way, using artificial intelligence, through the collection of vital signs, pathologies and health conditions (diabetes, asthmatics, hypertension, etc.) of the individuals themselves. The expected result is to have a useful tool for collective health systems that assists decision-making and allows the reduction of those contaminated by the COVID virus19.

The use of the application is only allowed for people over 18 years old. To register, you must accept the term TCLE / TALE. All people can abandon the research at any time, just do not update their measurements, which leaves their participation inactive, and the data will be erased during the next processing.

It is important that you follow the five steps below:
1. Must have a thermometer.
2. You must fill in all the required personal information.
3. When making a new measurement, you must measure 3 (three) vital signs and record each one of them in the system, as soon as measured. They are: temperature, respiratory rate and pulse. To measure the temperature, it is estimated 5 minutes. In the other two vital signs (respiratory rate and pulse) the estimated time is 60 seconds.
4. Next, it is necessary to register each of the pathologies and / or illnesses that you present at the time of the measurement, please ignore pre-existing symptoms.
5. When recording the measurement, it will be possible to track your history, as well as what risk situation you are in.

The results of your data will be presented in university papers and in research journals, but without identifying your participation. Nothing will have your name or other information that identifies you.

The results of your monitoring will be in your application's history only as long as you actively participate in the survey. Your non-updated data will be automatically deleted from the computers of the School of Science and Technology of the Federal University of Rio Grande do Norte - UFRN, in order to ensure your privacy.

It is important to highlight that, this study does not perform a clinical diagnosis, but, it helps the participant in the understanding of the signs and symptoms related to the disease and works together with the public health agencies to investigate epidemiological diseases in their community.

Correções:

- Resolvido o problema de travamento dos campos de cadastro e edição dos dados do usuário ao digitar um CEP inválido ou em caso de não conseguir definir os campos automaticamente.

Allows applications to open network sockets.