Whom to avoid?

Inspiration

I was inspired by the bleak scenario surrounding me currently, as I realised that a majority of doctor's time is used for diagnosis. With this app, patient diagnosis will become easier and healthcare services can be provided to a larger number of consumers. I was also motivated to move beyond the stereotypical 'green' technological solutions that are commonly suggested for the theme of sustainability. Although this app largely pertains to the medical field, it is sustainable because it has long-term potential and effectively uses technology to create an environment where all elements are efficiently allocated.

What it does

This app takes into consideration the user's medical history, average oxygen levels, doctor's appointments and comments, medical prescriptions, any medical reports available and the user's regular habits. Using all this data, it will determine any possible health risks to the user, with a special emphasis on the repiratory health owing to the extenuating circumstances of Covid-19. Once a threshold for Covid-19 exposure is predicted, the app will alert the user every time they are in close proximity of a patient, or possible asymptomatic carrier. However, this may be a cause for concern, as the user may feel that their privacy is compromised, since this would require constant location tracking. Hence, this needs to be discussed with possible users in order to trule gauge what level of security they can expect. A possible solution to this could also be restricting the personal details of others in the user interface and only releasing it on a need-to-know basis. A critical aspect of this project was outliers, since instead of eliminating outliers from the model, this model focuses specifically on outliers and any anomalous behaviour of the user's health is accounted for.

Challenges I ran into

The main challenge has been prioritising different aspects of the project, since this project was developed over 2 days. I resolved this challenge by focusing on planning the project and reflecting on it rather than coding it, which would have diverted my attention. Another challenge was determining a balance between maintaining user privacy, and creating a model that learns from its users. A possible solution to this could be data encryption and restricting user access.

Accomplishments that I'm proud of

I am proud of the fact that my project is based on service, and giving back to the community since, according to me, that is the most important and understated aspect of any project we undertake. Not only this, but the video-editing process made me more aware of my self-growth. This project was a lot of fun, and tested my STEAM skills, making me more aware of my strengths and weaknesses, for which I am truly grateful.

What I learned

I learned a lot about the challenge faced by the healthcare sector on a regular basis- even before the pandemic- and it made me appreciate them even more. While researching for this project, my attention was also drawn towards all the different jobs within the medical sector, other than doctors, which do not receive enough recognition for their hardwork.

What's next for Whom to avoid?

Next, I intend to work on developing the app and actually implementing this design using machine learning. A challenge I will probably face in this process is getting sufficient training and testing data for hgih accuracy. After the preliminary testing is done, I hope to release it by December 2020, to meet the urgent needs of people.

Built With

• python