ArticleJMIR medical informatics2017
Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure.
Article in JMIR medical informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
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- COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning.Briefings in bioinformatics · 2022Article
- Application of Improved LSTM Algorithm in Macroeconomic Forecasting.Computational intelligence and neuroscience · 2021Article
- Compensated Fuzzy Neural Network-Based Music Teaching Ability Assessment Model.Computational intelligence and neuroscience · 2021Article
- Exchange Rate Forecasting Based on Deep Learning and NSGA-II Models.Computational intelligence and neuroscience · 2021Article
- Construction of the Reverse Resource Recovery System of e-Waste Based on DLRNN.Computational intelligence and neuroscience · 2021Article
- Sports Training System Based on Convolutional Neural Networks and Data Mining.Computational intelligence and neuroscience · 2021Article
- Optimization of Data Mining and Analysis System for Chinese Language Teaching Based on Convolutional Neural Network.Computational intelligence and neuroscience · 2021Article
- Performance Evaluation of Enterprise Supply Chain Management Based on the Discrete Hopfield Neural Network.Computational intelligence and neuroscience · 2021Article
- 3D Virtual Reality Implementation of Tourist Attractions Based on the Deep Belief Neural Network.Computational intelligence and neuroscience · 2021Article
- Safety Risk Assessment of Tourism Management System Based on PSO-BP Neural Network.Computational intelligence and neuroscience · 2021Article
- Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network.Computational intelligence and neuroscience · 2021Article
- Analysis of Sports Performance Prediction Model Based on GA-BP Neural Network Algorithm.Computational intelligence and neuroscience · 2021Article
- Optimization of Online Education and Teaching Evaluation System Based on GA-BP Neural Network.Computational intelligence and neuroscience · 2021Article
- Identification of Adverse Drug Event-Related Japanese Articles: Natural Language Processing Analysis.JMIR medical informatics · 2020Article
- Discovering the Context of People With Disabilities: Semantic Categorization Test and Environmental Factors Mapping of Word Embeddings from Reddit.JMIR medical informatics · 2020Article
- Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project.Drug safety · 2020Article
- Adverse Drug Events and Contributing Factors Among Hospitalized Adult Patients at Jimma Medical Center, Southwest Ethiopia: A Prospective Observational Study.Current therapeutic research, clinical and experimental · 2020Article
- Application of Augmented Intelligence for Pharmacovigilance Case Seriousness Determination.Drug safety · 2020Article
- A review of big data and medical research.SAGE open medicine · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundThe study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs.
objectiveThe aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs.
methodsWe analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural language processing, and machine learning. This was combined with an Elasticsearch No-SQL distributed database to explore and visualize ADEs.
resultsThe accuracy, precision, recall, and area under receiver operating characteristic of the system were 92.7%, 93.6%, 93.0%, and 0.905, respectively, and showed better results in comparison with traditional approaches in the literature. This work not only detected and classified ADE sentences from big data biomedical literature but also scientifically visualized ADE interactions.
conclusionsTo the best of our knowledge, this work is the first to investigate a big data machine learning strategy for ADE discovery on massive datasets downloaded from PubMed Central and social media. This contribution illustrates possible capacities in big data biomedical text analysis using advanced computational methods with real-time update from new data published on a daily basis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.