SBIR Phase I: Deep learning diagnosis and platform for at-home ear evaluations in children

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I Project will improve pediatric health. Pediatric ear infections often manifest at night and the child must wait until the next day for an evaluation and treatment. The intention of this project is to create a deep-learning at-home ear infection diagnostic system.

This Small Business Innovation Research (SBIR) Phase I will advance translation of a pediatric ear-imaging system. The objectives include: generating a training data set with images labeled with correct diagnoses from a pediatric clinical setting; creating a deep learning algorithm with transfer learning from well-established convolutional neural networks for prediction; creating a prototype software interface to label a new image presented to the system; and designing a speculum for at-home image acquisition.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.