Published on 27.06.14 in Vol 2, No 1 (2014): Jan-Jun
Works citing "Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives"
According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.3022):
(note that this is only a small subset of citations)
-
Munkhdalai T, Liu F, Yu H. Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning. JMIR Public Health and Surveillance 2018;4(2):e29
CrossRef -
Nikfarjam A, Sarker A, O’Connor K, Ginn R, Gonzalez G. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features. Journal of the American Medical Informatics Association 2015;22(3):671
CrossRef -
Routray R, Tetarenko N, Abu-Assal C, Mockute R, Assuncao B, Chen H, Bao S, Danysz K, Desai S, Cicirello S, Willis V, Alford SH, Krishnamurthy V, Mingle E. Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination. Drug Safety 2020;43(1):57
CrossRef -
Alvaro N, Miyao Y, Collier N. TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations. JMIR Public Health and Surveillance 2017;3(2):e24
CrossRef -
Beeksma M, Verberne S, van den Bosch A, Das E, Hendrickx I, Groenewoud S. Predicting life expectancy with a long short-term memory recurrent neural network using electronic medical records. BMC Medical Informatics and Decision Making 2019;19(1)
CrossRef -
Terrier J, Daali Y, Fontana P, Csajka C, Reny J. Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants. Clinical Pharmacokinetics 2019;58(12):1517
CrossRef -
Li F, Liu W, Yu H. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. JMIR Medical Informatics 2018;6(4):e12159
CrossRef -
Abatemarco D, Perera S, Bao SH, Desai S, Assuncao B, Tetarenko N, Danysz K, Mockute R, Widdowson M, Fornarotto N, Beauchamp S, Cicirello S, Mingle E. Training Augmented Intelligent Capabilities for Pharmacovigilance: Applying Deep-learning Approaches to Individual Case Safety Report Processing. Pharmaceutical Medicine 2018;32(6):391
CrossRef -
Liu F, Jagannatha A, Yu H. Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records. Drug Safety 2019;42(1):95
CrossRef -
Kaas‐Hansen BS, Placido D, Rodríguez CL, Thorsen‐Meyer H, Gentile S, Nielsen AP, Brunak S, Jürgens G, Andersen SE. Language‐agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records. Basic & Clinical Pharmacology & Toxicology 2022;131(4):282
CrossRef -
Gaspar F, Lutters M, Beeler PE, Lang PO, Burnand B, Rinaldi F, Lovis C, Csajka C, Le Pogam M. Automatic Detection of Adverse Drug Events in Geriatric Care: Study Proposal. JMIR Research Protocols 2022;11(11):e40456
CrossRef -
T S, T C, MARPAKA S, K S. ASPECTS OF UTILIZATION AND LIMITATIONS OF ARTIFICIAL INTELLIGENCE IN DRUG SAFETY. Asian Journal of Pharmaceutical and Clinical Research 2021;:34
CrossRef -
Roosan D, Law AV, Roosan MR, Li Y. Artificial Intelligent Context-Aware Machine-Learning Tool to Detect Adverse Drug Events from Social Media Platforms. Journal of Medical Toxicology 2022;18(4):311
CrossRef -
Zitu MM, Zhang S, Owen DH, Chiang C, Li L. Generalizability of machine learning methods in detecting adverse drug events from clinical narratives in electronic medical records. Frontiers in Pharmacology 2023;14
CrossRef
According to Crossref, the following books are citing this article (DOI 10.2196/medinform.3022):