Inspiration

When the "Health and AI" theme came out, I knew that a great way to combine the two fields was to diagnose allergies. The idea for EaseAllergies came from allergy symptoms that my friends in school suffered from. A great way to be able to take effective treatment for alleries is to monitor how, in the past, certain allergy levels in the environment led to certain symptoms. So, EaseAllergies combines a patient's medical history with pollen level forecast, to be able to predict when you will suffer from allergies, what symptoms you will experience, and what drug you should take to avoid/stop suffering from allergies.

What it does

EaseAlleries holds a database that contains patient medical information and their medical history. Each patient has a triggering pollen level, or a pollen level above which they suffer allergy symptoms. This patient First, EaseAllergies web scrapes pollen level data and the weather in the environment from the Internet. Then, the program compares the pollen level that is in the atmosphere and determines whether the atmosphere is dangerous and will lead to allergy suffering. If the pollen level will lead to allergies, the program will refer to the medical history table in the database and search for other times when the patient has suffered from allergies. It will analyze the symptoms, treatments, and whether the treatment worked to determine a solution. This solution predicts the symptoms that the patient may suffer from and suggests a drug treatment that should be used (because it has worked in the past). Next, the program sends a text message to the patient outlining all this information (pollen forecast, prediction of symptoms, treatment suggestion). This makes it easy and quick for patients to get a heads-up on how their allergies can be prevented in the week. Next, the web application aspects allows for user interaction with EaseAllergies. This contains three platforms, the patient, doctor, and pharmacy side. The patient webpage allows patients to enter whatever allergies they suffered from. They can enter their name, triggering pollen level, the triggering weather, symptoms, treatment they took, and whether the drug worked. This information is stored in their medical history in the database. The doctor UX allows for doctors to log on to EaseAllergies and monitor the health of their patients. On that webpage, they can view a list of all allergy entries from the database, including what symptoms their patients suffered from, the pollen and weather level that triggered the allergy, the drug taken, and whether the treatment worked. This way, if needed, the doctors can contact their patients if they need to prescribe a drug or meet with them for an allergy appointment. The pharmacy UX utilizes sample data to plot analytics that measures pollen allergy cases and how they are growing by the day. In addition, it presents data on what drugs are being used by customers. This way, pharmacies can plan ahead and make sure that specific drugs are in stock on specific days. This allows for prediction of when allergy drugs will be in most demand.

How I built it

I built it using a database architecture in PostgreSQL. I use a web server built with Node and Express.js. I perform string concatenation, computations, webscraping, and text message sending in Python. Finally, I use HTML, CSS, and JavaScript to make the webpage.

Challenges I ran into

I ran into challenges while compiling a text message and sending it. I also ran into a challenge when trying to allow for the patient to write to their medical history.

Accomplishments that I'm proud of

A successful text message is sent, a full stack web application is made, and the database patient information and allergy history can be successfully presented to suggest treatment and symptoms.

What I learned

I learned a lot about how to combine python and Node.js. I need to work on my skills of sending JSON information from a Python script to Javascript.

What's next for EaseAllergies

  1. User profile for each patient
  2. Numerical representation and analysis of pollen levels
  3. Implement pharmacy side more rigorously
  4. Allow for text message readability
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