TXT MD

Diagnoses viral illnesses over SMS || Epidemic tracking.

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Technologies Used

Big Data

Project Team

Hamzah Randhawa
Developer
Keeran
Developer Designer
Burhan Qadri
Developer
Umar Ahmed
Developer Designer

This team is looking for

Product Manager Investor
REQUEST TO JOIN

About

// PLEASE SEE LINK // *** http://ow.ly/j0u2301IGcq *** || Code4Impact Award Winner at AngelHack Toronto || // THE PROBLEM // Mechanisms for detecting and tracking epidemics currently trail the epidemic by one week, according to the CDC, leading to a reactive response, not proactive. In a parallel problem, for disadvantaged groups due to inequality (including rural residents and women) access to healthcare is difficult and comes at a high opportunity cost. As a result 40% - 60% (according to county) regularly forego getting symptoms checked, and in addition lack medical histories and knowledge about hygiene and disease prevention. // WHAT IS IT // Harnessing the power of SMS and countries' Open Data initiatives, TXT MD combats poor access to healthcare and the difficulty of detecting and tracking epidemics in real time by doing two things: 1. Diagnose viral diseases remotely from symptoms. 2. Use big data and machine-learning in a new way to identify patterns in diagnoses and detect epidemic before it spreads and alert relevant agencies and users. // CONVENIENCE // Alongside these features are a host of others designed to solve problems. It is easy to spread, having a five-digit phone code. The intelligent service is accessible, requiring no internet and available in different languages. The symptoms checklist is split into levels of depth, going deeper to completely understand the user's condition; concurrently it is designed to be at a minimal cost to the user. It creates medical histories where there were previously none; it assigns patients to streams of tips in order to become a regular part of their lives. It can send daily reports [with anonymized data] to healthcare NGOs and aid agencies. In the event of an epidemic detection, it alerts agencies and users in affected areas, pointing them to treatment centers and providing crucial information. In terms of design, it is simple, it is accessible, and it is powerful, on a platform that every mobile user has extensive experience with. // MACHINE LEARNING // It is constantly learning, improving from the spread patterns of every disease, as well as from the aggregate data. We are consumed with passion about where this can go. This is an equalizer, and will impact real lives. *** https://www.youtube.com/watch?v=QI9mRRtXVaY *** // REPORT || HOW IT WORKS // To answer any and all of your questions, the following is a link to our report detailing the specifics of our services, our target audience, our sustainable business model, our [developed and planned] features and our next steps for growth. Please do check it out, you won't be disappointed: *** https://goo.gl/l3dKfs ***

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