Utilizing AI and Social Media Analytics to Discover Adverse Side Effects of GLP-1 Receptor Agonists

arXiv:2404.01358v1 Announce Type: cross
Abstract: Adverse side effects (ASEs) of drugs, revealed after FDA approval, pose a threat to patient safety. To promptly detect overlooked ASEs, we developed a digital health methodology capable of analyzing massive public data from social media, published clinical research, manufacturers' reports, and ChatGPT. We uncovered ASEs associated with the glucagon-like peptide 1 receptor agonists (GLP-1 RA), a market expected to grow exponentially to $133.5 billion USD by 2030. Using a Named Entity Recognition (NER) model, …

abstract analytics arxiv clinical clinical research cs.ai cs.cl cs.ir cs.lg cs.si data digital digital health drugs effects fda fda approval health massive media methodology patient public public data q-bio.qm research safety social social media social media analytics threat type