Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature
暂无分享,去创建一个
[1] Daniel N. Sosa,et al. Contexts and contradictions: a roadmap for computational drug repurposing with knowledge inference , 2022, Briefings Bioinform..
[2] K. Boyack,et al. Massive covidization of research citations and the citation elite , 2022, medRxiv.
[3] Q. Zhou,et al. Knowledge Graph-Based Approaches to Drug Repurposing for COVID-19 , 2021, J. Chem. Inf. Model..
[4] Stefano E. Rensi,et al. Repurposing biomedical informaticians for COVID-19 , 2021, Journal of Biomedical Informatics.
[5] Masayasu Atsumi,et al. Pre-training a BERT with Curriculum Learning by Increasing Block-Size of Input Text , 2021, RANLP.
[6] R. Altman,et al. Analyzing the vast coronavirus literature with CoronaCentral , 2020, bioRxiv.
[7] J. Ioannidis,et al. The rapid, massive growth of COVID-19 authors in the scientific literature , 2020, bioRxiv.
[8] J. Nemunaitis,et al. FDA efficiency for approval process of COVID-19 therapeutics , 2020, Infectious agents and cancer.
[9] P. Slomka,et al. Preprint manuscripts and servers in the era of coronavirus disease 2019. , 2020, Journal of evaluation in clinical practice.
[10] Yongdong Zhang,et al. Curriculum Learning for Natural Language Understanding , 2020, ACL.
[11] Debojyoti Moulick,et al. Evaluating the potential of different inhibitors on RNA-dependent RNA polymerase of severe acute respiratory syndrome coronavirus 2: A molecular modeling approach , 2020, Medical Journal Armed Forces India.
[12] J. Qu,et al. Hydroxychloroquine in patients with mainly mild to moderate coronavirus disease 2019: open label, randomised controlled trial , 2020, BMJ.
[13] D. Wang,et al. Hydroxychloroquine application is associated with a decreased mortality in critically ill patients with COVID-19 , 2020, medRxiv.
[14] Oren Etzioni,et al. CORD-19: The Covid-19 Open Research Dataset , 2020, NLPCOVID19.
[15] S. Anzick,et al. Clinical benefit of remdesivir in rhesus macaques infected with SARS-CoV-2 , 2020, Nature.
[16] M. Mckee,et al. Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018. , 2020, JAMA.
[17] Lysandre Debut,et al. HuggingFace's Transformers: State-of-the-art Natural Language Processing , 2019, ArXiv.
[18] Jaewoo Kang,et al. BioBERT: a pre-trained biomedical language representation model for biomedical text mining , 2019, Bioinform..
[19] Russ B. Altman,et al. A Literature-Based Knowledge Graph Embedding Method for Identifying Drug Repurposing Opportunities in Rare Diseases , 2019, bioRxiv.
[20] Omer Levy,et al. RoBERTa: A Robustly Optimized BERT Pretraining Approach , 2019, ArXiv.
[21] Konrad Paul Kording,et al. Claim Extraction in Biomedical Publications using Deep Discourse Model and Transfer Learning , 2019, arXiv.org.
[22] Wei-Hung Weng,et al. Publicly Available Clinical BERT Embeddings , 2019, Proceedings of the 2nd Clinical Natural Language Processing Workshop.
[23] Iz Beltagy,et al. SciBERT: A Pretrained Language Model for Scientific Text , 2019, EMNLP.
[24] P. Sanseau,et al. Drug repurposing: progress, challenges and recommendations , 2018, Nature Reviews Drug Discovery.
[25] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[26] Alexey Romanov,et al. Lessons from Natural Language Inference in the Clinical Domain , 2018, EMNLP.
[27] Kawin Ethayarajh,et al. Unsupervised Random Walk Sentence Embeddings: A Strong but Simple Baseline , 2018, Rep4NLP@ACL.
[28] Samuel R. Bowman,et al. A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference , 2017, NAACL.
[29] Jacob K. Asiedu,et al. The Drug Repurposing Hub: a next-generation drug library and information resource , 2017, Nature Medicine.
[30] Dexter Hadley,et al. Systematic integration of biomedical knowledge prioritizes drugs for repurposing , 2017, bioRxiv.
[31] Mark Stevenson,et al. A corpus of potentially contradictory research claims from cardiovascular research abstracts , 2016, J. Biomed. Semant..
[32] Eric Gilbert,et al. VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text , 2014, ICWSM.
[33] Yong-Jian Wu,et al. Fish consumption and incidence of heart failure: a meta-analysis of prospective cohort studies. , 2013, Chinese medical journal.
[34] Hsin-Chieh Yeh,et al. Effect of the 2011 vs 2003 duty hour regulation-compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. , 2013, JAMA internal medicine.
[35] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[36] Paul A. Fontelo,et al. Utilization of the PICO framework to improve searching PubMed for clinical questions , 2007, BMC Medical Informatics Decis. Mak..