Identifying epilepsy surgery referral candidates with natural language processing in an Australian context.
Sheryn TanRudy GohJeng Swen NgCharis TangCleo NgJoshua KovoorBrandon StrettonAashray GuptaChristopher OvendenMerran R CourtneyAndrew NealEmma WhithamJoseph FrascaMichelle KileyAmal Abou-HamdenStephen BacchiPublished in: Epilepsia open (2024)
Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred. Machine learning-natural language processing demonstrates promising results in assisting with the identification of such suitable candidates in Australia.