{"doi":"10.1145/3539618.3591897","title":"BioSift: A Dataset for Filtering Biomedical Abstracts for Drug Repurposing and Clinical Meta-Analysis","abstract":"This work presents a new, original document classification dataset, BioSift, to expedite the initial selection and labeling of studies for drug repurposing. The dataset consists of 10,000 human-annotated abstracts from scientific articles in PubMed. Each abstract is labeled with up to eight attributes necessary to perform meta-analysis utilizing the popular patient-intervention-comparator-outcome (PICO) method: has human subjects, is clinical trial/cohort, has population size, has target disease, has study drug, has comparator group, has a quantitative outcome, and an \"aggregate\" label. Each abstract was annotated by 3 different annotators (i.e., biomedical students) and randomly sampled abstracts were reviewed by senior annotators to ensure quality. Data statistics such as reviewer agreement, label co-occurrence, and confidence are shown. Robust benchmark results illustrate neither PubMed advanced filters nor state-of-the-art document classification schemes (e.g., active learning, weak supervision, full supervision) can efficiently replace human annotation. In short, BioSift is a pivotal but challenging document classification task to expedite drug repurposing. The full annotated dataset is publicly available and enables research development of algorithms for document classification that enhance drug repurposing.","journal":"PubMed","year":2023,"id":396881,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":29.844511487584125,"corpus_rank":8690,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.943,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":987366,"name":"Irfan Al-Hussaini","orcid":"0000-0003-2969-7019","position":1,"is_corresponding":false},{"id":822710,"name":"H Turner","orcid":"0009-0006-7198-714X","position":2,"is_corresponding":false},{"id":1172547,"name":"Jennifer Deng","orcid":"0009-0008-5239-5653","position":3,"is_corresponding":false},{"id":1172548,"name":"Shubham Lohiya","orcid":"0009-0002-7703-0462","position":4,"is_corresponding":false},{"id":1172549,"name":"Prasanth Bathala","orcid":"0009-0003-4457-5412","position":5,"is_corresponding":false},{"id":490400,"name":"Cassie S. Mitchell","orcid":"0000-0002-5472-6355","position":6,"is_corresponding":false},{"id":688415,"name":"David Kartchner","orcid":"0000-0003-1937-1840","position":0,"is_corresponding":true}],"reference_count":35,"raw_metadata":null,"created_at":"2026-07-19T01:19:35.497854Z","pmid":"38690157","pmcid":"PMC11060830","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}