Medical Assistance Accessibility Tool

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Inspiration

We were inspired to create the Medical Assistance Accessibility Tool (MAAT) after seeing BGB's prompt and acknowledging that people we knew ourselves had trouble navigating the healthcare industry.

We wanted to create a tool that could help all patients, regardless of their technical expertise or health literacy, to access and understand the medical information they need. We also wanted to create a tool that could help patients to communicate more effectively with their doctors.

What it does

MAAT is a web-based platform that uses artificial intelligence to make medical information more accessible and understandable for everyone. It offers a variety of features, including:

Speaking to a physician: Patients are able to click a button when they’d like to start speaking, and click it once more when they’d like to stop. Transcription of the audio a patient says will then be returned in live time, and answered via an artificial intelligence language model trained for proficiency in the medical field. They can continue to chat and communicate further to the bot as they will, until they feel comfortable enough with the satisfaction of their medical inquiries, which they can then communicate to their doctor when they come in for a visit, in a way that they understand themselves.

Summarization of complex medical information: Patients are able to click a button when they’d like to start speaking, and click it once more when they’d like to stop. This audio will be interpreted by a separate artificial intelligence language model, trained to simplify complex medical information into “layman’s” terms. The use case of this can be applied live during a Doctor's visit, at home when taking a look at diagnosis, or in any case when a patient wishes to speak medical information allowed and receive it in a more easily interpreted way.

How we built it

MAAT was built using a variety of technologies, including:

HTML, CSS, and JavaScript for the frontend Python and Flask for the backend Dialogflow for the natural language processing WebKitSpeech Recognition for the speech recognition ChatGPT for the conversational AI capabilities We also used a variety of open source libraries and frameworks, such as React, Redux, and Bootstrap.

Challenges we ran into One of the biggest challenges we faced was integrating all these technologies together.

Accomplishments that we're proud of We are proud to have created a platform that is making medical information more accessible and understandable for everyone. We are also proud that MAAT is designed to be accessible to people with disabilities.

What we learned

We learned a lot about artificial intelligence and natural language processing while developing MAAT. We also learned a lot about the challenges that patients face when trying to access and understand medical information.

We also learned the importance of user testing and feedback. We involved patients and healthcare professionals in the development process from the beginning, and their feedback helped us to create a platform that is truly useful.

What's next for Medical Assistance Accessibility Tool

We are currently working on adding new features to MAAT, such as the ability to generate personalized treatment plans and to connect patients with clinical trials. We are also working on making MAAT available in more languages.

We are committed to making MAAT the best platform it can be for helping patients to access and understand the medical information they need. We believe that MAAT has the potential to make a real difference in the lives of patients around the world.

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