TY - JOUR AU - Nordon, Galia AU - Koren, Gideon AU - Shalev, Varda AU - Horvitz, Eric AU - Radinsky, Kira PY - 2019/07/17 Y2 - 2024/03/28 TI - Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 33 IS - 01 SE - IAAI Technical Track: Emerging Papers DO - 10.1609/aaai.v33i01.33019565 UR - https://ojs.aaai.org/index.php/AAAI/article/view/5017 SP - 9565-9572 AB - <p>We present a system that jointly harnesses large-scale electronic health records data and a concept graph mined from the medical literature to guide drug repurposing—the process of applying known drugs in new ways to treat diseases. Our study is unique in methods and scope, per the scale of the concept graph and the quantity of data. We harness 10 years of nation-wide medical records of more than 1.5 million people and extract medical knowledge from all of PubMed, the world’s largest corpus of online biomedical literature. We employ links on the concept graph to provide causal signals to prioritize candidate influences between medications and target diseases. We show results of the system on studies of drug repurposing for hypertension and diabetes. In both cases, we present drug families identified by the algorithm which were previously unknown. We verify the results via clinical expert opinion and by prospective clinical trials on hypertension.</p> ER -