The problem HealthifAI solves

Healthcare is one of the most important and critical industries in the world. Providing quality medical care to patients is essential, but it is often hindered by various challenges such as overburdened healthcare workers, lack of medical devices in rural areas, and administrative stress. With the advent of artificial intelligence and machine learning, the healthcare industry has a unique opportunity to tackle these challenges head-on and revolutionize the way medical care is delivered.

With this as context, we plan to tackle the Provider Shortage & Burnout and Access to Care strategic themes.

HealthifAI aims to tackle several key pain points in the healthcare industry - specifically for the following :

Provider Shortage & Burnout :

Intuitive, easy & safe digital patient record entry which eliminates the need for manual and legacy record entry methods.
We provide an ML-powered "soft diagnosis" to save time for doctors and nurses.
We have location-based COVID-19 alerts to better equip workers.
Multilingual speech-to-text notes, because it's easier!
Reminder system to help with medication/check-ups. Keeping track of everything is hard!

Access to care :
Multilingual communication model that transcribes speech from any language into English. This is particularly helpful in rural areas where communication is a barrier.
Experimental Computer-Vision powered heart rate monitor. This transforms everyday hand-held devices into medical devices - an exciting vision for the future!

HealthifAI was built using cutting-edge AI and machine learning technologies, including Open-AI and Flask. The team used the Flask framework to build a RESTful API that can handle incoming requests and return appropriate responses. We used React.js & Tailwind as CSS framework. The Authentication (OAuth) has been done by Firebase & we’re also using the Cloudstore database for storing user logs.

The API was integrated with the Open-AI speech-to-text model using KANDI KITS

Challenges we ran into

Building HealthifAI was not without its challenges. One of our challenges was integrating the various AI and machine learning technologies into a cohesive and functional system. This required a deep understanding of each technology, as well as expertise in data processing and software engineering.