Overview

这个项目是一个5个小时KCL校内黑客松的项目，灵感来自Sarah，他认为留学生需要一个这样的APP来解决看病的问题。

站在我个人的角度这个还是非常实用的，有趣的是我们做这个项目的时候在最后30秒的时候极限提交，差一点点就白白浪费了5小时时间。

最终我们也成功获得了TOP3。

Implemented Highlights

• AI emergency locator for nearby A&E, urgent care, and hospitals.
• Insurance-aware filtering for NHS/IHS/private coverage options.
• QuickRoute ranking by total time to be seen, not just nearest distance.
• Safety triage gate for life-threatening symptoms with 999 guidance.
• Context checklist for documents, medication, and emergency contacts.
• After-visit guidance for GP registration, prescriptions, and follow-up.

Decision Flow

• Symptom assessment classifies urgency (severe / moderate / mild).
• Coverage filter narrows hospitals based on insurance access rules.
• Travel-time service computes driving/transit/walking durations.
• Wait-time + travel-time are combined to rank the best choice.
• LLM function generates a concise human-readable recommendation reason.

Team

• Yuzhen (Max) Yang
• Shian (Andy) Ye
• Sarah Asulaim
• Zhewen (Ryan) Zheng

Project Link

Open GitHub repository

Features

• Emergency locator with map-based nearby hospital discovery
• Insurance and access filter for NHS, IHS, and private scenarios
• QuickRoute recommendation based on total time to be seen
• One-tap language switch for international accessibility

The recommendation layer combines travel-time data, wait-time estimates, and concise LLM explanations to improve emergency decisions.

Technologies

Python · Flask · Computer Vision · Generative AI