FORESIGHT: A Dataset for Forecasting Eye Surgery Outcomes Using AI
Main Goal: To facilitate research on the outcomes of refractive surgeries. Specific aim: To transform the available raw data into an organized dataset that is readily available for analysis by clinical researchers. Background: Cataract and refractive surgery is the most commonly performed type of eye surgery, whereby half of the general population will have it at some point of their life. Each year, over 30 million are performed worldwide. The outcome of said surgery depends heavily on the surgeon’s ability to predict the postoperative visual acuity of the patient. The past 15 years have witnessed a rapid advancement of predictive technologies such as ablative procedure nomograms and intraocular lens (IOL) power calculators. With the increasing accessibility of artificial intelligence (AI), newer prognostic models have emerged, but their usability in the clinic remains limited. This hindrance is owed to the lack of external validation, which in its turn requires on the availability of outcomes datasets that are ready for analysis. The raw data is based on a HIPAA-compliant back-up of an electronic medical records (EMR) system provided by the leading center for cataracts and refractive surgery in the greater Boston and east Massachusetts area. The raw data contains 13 years worth of longitudinal data.
Desired Disciplines
- Medicine, Engineering, Computer Science, Bioinformatics, Data Analytics
Team Leader
Industry Partners
- Boston Vision