README
HopHacks2023
In today's healthcare landscape, the synergy between doctors and patients often encounters inefficiencies and delays. Despite advancements, the rate of diagnostic inaccuracies remains disconcertingly consistent, compromising patient outcomes. These diagnostic challenges arise primarily from two interconnected issues: the scarcity of comprehensive patient data available to doctors and the burdensome demands on already stretched medical teams.
These overlapping challenges diminish the richness of patient-doctor interactions during clinical visits. This is where our pioneering app comes into play. Our platform empowers patients by enabling them to interact with an AI-driven chatbot that comprehensively assesses their symptoms. Integrated seamlessly with the Apple iPhone and Apple Watch Health Apps, it harnesses real-time health metrics, ensuring a holistic understanding of a patient's wellbeing. By sharing this comprehensive health snapshot with their healthcare providers before appointments, patients can enrich their consultations, providing a foundation for more informed decisions. The result? Improved diagnostic precision, more efficient patient-doctor dialogues, and a notable reduction in healthcare costs.
Getting Started
Dependencies
- Please refer to the requirements.txt file for all dependencies
Installing
If running locally, ensure that you have all items installed from requirements.txt installed within your virtual environment.
You will need to add a .env file to the root directory with the following variables:
- OPENAI_API_MODEL
- OPENAI_API_KEY
From the root directory, run the following command:
streamlit run Home.py
Navigate to the localhost link provided in the terminal to view the application.
If running via share.streamlit.io, simply navigate to the following link:
Authors
Contributors names and contact info
William Kourafas [Git: controversy7]
Jonathan Samuel [Git: samuelJon17]
Maria Valverde [Git: mvalver2]
Daniel Nashed [Git: danielnashed]
Version History
- Initial Release: September 17, 2023
Contributors
Similar repos
Languages
Jupyter Notebook
56.8%
Python
43.2%
README
HopHacks2023
In today's healthcare landscape, the synergy between doctors and patients often encounters inefficiencies and delays. Despite advancements, the rate of diagnostic inaccuracies remains disconcertingly consistent, compromising patient outcomes. These diagnostic challenges arise primarily from two interconnected issues: the scarcity of comprehensive patient data available to doctors and the burdensome demands on already stretched medical teams.
These overlapping challenges diminish the richness of patient-doctor interactions during clinical visits. This is where our pioneering app comes into play. Our platform empowers patients by enabling them to interact with an AI-driven chatbot that comprehensively assesses their symptoms. Integrated seamlessly with the Apple iPhone and Apple Watch Health Apps, it harnesses real-time health metrics, ensuring a holistic understanding of a patient's wellbeing. By sharing this comprehensive health snapshot with their healthcare providers before appointments, patients can enrich their consultations, providing a foundation for more informed decisions. The result? Improved diagnostic precision, more efficient patient-doctor dialogues, and a notable reduction in healthcare costs.
Getting Started
Dependencies
- Please refer to the requirements.txt file for all dependencies
Installing
If running locally, ensure that you have all items installed from requirements.txt installed within your virtual environment.
You will need to add a .env file to the root directory with the following variables:
- OPENAI_API_MODEL
- OPENAI_API_KEY
From the root directory, run the following command:
streamlit run Home.py
Navigate to the localhost link provided in the terminal to view the application.
If running via share.streamlit.io, simply navigate to the following link:
Authors
Contributors names and contact info
William Kourafas [Git: controversy7]
Jonathan Samuel [Git: samuelJon17]
Maria Valverde [Git: mvalver2]
Daniel Nashed [Git: danielnashed]
Version History
- Initial Release: September 17, 2023
Similar repos
Contributors
Languages
Jupyter Notebook
56.8%
Python
43.2%