Biomedical information retrieval

Abstract

It is well known that the volume of biomedical literature is growing exponentially and that scientists are being overwhelmed when they sift through the scope and diversity of this unstructured knowledge to find relevant information. TREC Precision Medicine 2017 is a track focusing on retrieving relevant scientific abstract and clinical trials from PubMed and Clinicaltrails.gov for cancer patients given their medical case. This report describes the system architecture for the TREC 2017 Precision Medicine Track. I explored query expansion techniques using wellknown broad knowledge sources such as Metamap and Entrez database. I used different pseudo relevance feedback technique like TF-IDF, BO1 and Local Context Analysis to retrieve relevant medical abstracts. I have used hidden aspects of topic like precision medicine and treatment aspect to improve the scores. I report infNDCG, R-Prec and P@10 scores.