ChopperAI - self-care assistant

Inspiration

Every of our team members have had that "am I okay or not?" moment: strange symptoms, waiting forever, and no clear first step. We were also sensitive to how environment (heat waves, poor air, peak pollen) can exacerbate common problems and yet few of these symptom guides take environment into account. That led us to create CHOPPER and translate ambiguity into clear and appropriate first-step instructions without making a diagnosis.

What it does

CHOPPER is a rules-first, browser-based self-care assistant that:

Accumulates basics (age, biological sex, temperature, duration, chronic diseases)
Let users select grouped symptoms (head, respiratory, digestive, musculoskeletal system, nervous system, skin) and free-text.
Optionally uses your location (GPS or keyboard-entered location) to superimpose weather, air quality, and pollen for the duration of time you select.
- Can use clear triage engine to:
- Indicate red-flags (e.g., shortness of breath with chest pain)
- Rank likely common causes (e.g. common cold, allergy, migraine, gastro)
- Give basic steps, what to watch for, and when to obtain care
- Creates nearby next steps links (clinics/pharmacies) based on your location. Entirely client-side. No account or data base.

How we built it

First, our team planned to build an application, but the time is too limited, we switched to just making web-based program. We used 3 main languages, Javascript, HTML and CSS.

Challenges we ran into

Safety terminology: Introducing advice unequivocally without the implication of diagnosis; framing red-flag reasoning making the safe decision.
- Permissions & rate limits: Handling browser geolocation prompts and appropriate use of free APIs.
Clarity: Scannable sets of symptoms, yet specific enough to produce meaningful results.

Accomplishments that we're proud of

We are so proud of the final product that we managed to create for such limited time. Also, at the end, we are very happy that we can finish this challenge together.

What we learned

There are 2 things that we are most proud of. Firstly, we are able to appropriately apply APIs in our program (it performs extremely well. Secondly, the biggest and the most memorable thing that we learned is teamworking under time pressure.

What's next for ChopperAI - self-care assistant

There are many more features that we would very like to add in:

Clinical review & tuning: Rule set validation and extension with the collaboration of clinicians.
- Richer symptom model: Additional systems (ENT, dental, psychiatric clues), time patterns, and drug interactions.
- Personalization (private-first): Optional profiles (age bands, known conditions) maintained locally.
- Internationalization: Vietnamese/English and other locales with locale-aware care instructions.
- Accessibility & performance: Deeper audits (WCAG),screen-reader cues, and smaller bundles.
- PWA & offline: App-like experience; real-time weather if online and cached UI.
- Telehealth hand-off:Summary of context-rich information that can be conveyed with a clinician.