Application managed to get 80% accuracy following HIPAA and SOX standards
Meeting clients expectation in AI space and predictive analysis
Application helps to caution potential cardiac patients to take preventive steps
Client is one of the unique research laboratories in healthcare in the USA. They carry out research activities with the objective to find solutions for the welfare of human being through innovative technologies. One such experiment involves facial observation science to predict the occurrence or likeliness of cardiac arrest in the future. The client was in need of a pilot system as a mobile application to try it out at a hospital.
Client’s Challenges
The client was in search of a vendor specialized not only in AI space but in predictive analysis to obtain the required accuracy level using the given dataset.
Solution
After evaluating few vendors in the AI space the client decided to go with Hubino because of its core expertise in computer vision and data science. Hubino designed a mobile application using robust facial recognition algorithms which can detect minute details in the face to match with the dataset pattern and analyze the medical health records of the patients. Results are then matched with the actual data in the hospital to measure the accuracy level.
Value Proposition
The pilot application managed to record more than 80 percent success rate using facial observation metrics. The client was happy with the results. As a continuation to the study, improvisation on the dataset and metrics are in progress.
