Automated Fact-Checking of Articles Related to Neurodevelopmental Disorders

False claims or Fake News related to the healthcare or medicine field on Social Media have garnered increasing amounts of interest, especially in the aftermath of the COVID-19 pandemic. False claims about the pandemic which spread on social media have contributed to vaccine hesitancy and lack of trust in the advise of medical professionals. If not detected and disproved early, such claims can complicate future pandemic responses. We focus on false claims in the field of Neurodevelopmental Disorders (NDDs), which is an umbrella term for a group of disorders that includes Autism, ADHD, Cerebral Palsy, etc. In this paper we present our approach to automated systems for fact-checking medical articles related to NDDs. We also present an annotated dataset of 116 webpages which we use to test our model and present our results.