Healthcare │ Artificial Intelligence
Wovenware succeeds in creating a proof of concept for Best Option that validates a machine learning model capable of aiding in the process of selecting the right ulcer treatment.
Health professionals apply their expertise to determine the appropriate procedure to treat ulcers using their knowledge of both the patients and wounds. The decision-making process is complex given the quantity of available treatment options and the quantity of patient and wound characteristics that must be considered. leveraging high-performance
Best Option turned to Wovenware to run an innovation sprint and create a proof of concept for and AI predictive algorithm that could help health professionals with this decision process.
To address, Best Option’s goal was to validate the feasibility of improving the efficiency of health professionals through AI models Wovenware worked on a proof of concept with a sample data set and our Innovation Sprint methodology.
Technologies we take advantage of
Wovenware uses a sample data-set and Innovation Sprint to get it right the first time and develop an algorithm to help ensure it’s building the right thing by:
The proof of concept resulted in a validation of the feasibility of using machine learning models to aid health professionals in the decision-making process of selecting ulcer treatments. With 63%, 65% and 100% accuracy and p-values < 0.001, < 0.001, and 0.975 -0.2, all models may significantly improve with more sample data. Wovenware provided an assessment of the data requirements and next steps in order to build a more robust predictive model.