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CavMed About Page
Inspiration
The demise of Iyiola's Mom as a result of misdiagnosis and mis-prescription is the bedrock for our initiative to foster a more accurate outcomes to be presented by medical practitioners to Patients. We developed 3 AI- models that uses Deep learning as a means to give Predictive Analysis for accuracy in Diagnosis of illnesses such as Diabetes, Heart Failure and Lung Cancer.
What it does
Our Models provide predictive analysis about three major illnesses which are Diabetes, Heart Failure and Lung Cancer to coin accuracy for the improvement of the healthcare outcomes.
How we built it
We did our research on sample dataset from kaggle and we were able to get a good data to clean, explore and use for our modelling, we used deep learning to build three models which are were then deployed using streamlit and made different test, measures and errors. A flowchart was designed to understand users ability to discover, explore and utilize our products.
Challenges we ran into
Inaccurate data and data privacy.
Accomplishments that we're proud of
With the data set incorporated which is relevant up to 2022, we fed our AI models with these data to predict illness accuracy that gives outcomes around 88%,97% and 94% for diabetes, heart failure and Lung Cancer respectively.
What we learned
A new way to reshape the healthcare sector, the fear of patients lies in the inaccuracy of data and techniques to build AI- Medical practitioners relationship.
What's next for CavisMed-Orpheus-Snipers
Execution and improving the healthcare sectors in Nigeria by developing more Ai Models to foster accuracy in medical reports of patients on different illnesses.
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