ReviewChinese medical journal2016
Application and Exploration of Big Data Mining in Clinical Medicine.
Review in Chinese medical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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
24 citing papers in PubMed.
- Data Mining and Network Pharmacology Characterize Medication Patterns of Chinese Herbal Medicine for Bovine Viral Diarrhea.Veterinary sciences · 2026Article
- A decision rule algorithm for the detection of patients with hypertension using claims data.Journal of diabetes and metabolic disorders · 2025Article
- Outlier analysis for accelerating clinical discovery: An augmented intelligence framework and a systematic review.PLOS digital health · 2024Article
- Article
- Machine learning-based prediction model for the efficacy and safety of statins.Frontiers in pharmacology · 2024Article
- Machine learning models based on clinical indices and cardiotocographic features for discriminating asphyxia fetuses-Porto retrospective intrapartum study.Frontiers in public health · 2023Article
- Clinical decision support system for quality of life among the elderly: an approach using artificial neural network.BMC medical informatics and decision making · 2022Article
- Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study.JMIR medical informatics · 2021Article
- Fast prototyping of a local fuzzy search system for decision support and retraining of hospital staff during pandemic.Health information science and systems · 2021Article
- Decision Tree-Based Classification for Maintaining Normal Blood Pressure Throughout Early Adulthood and Middle Age: Findings From the Coronary Artery Risk Development in Young Adults (CARDIA) Study.American journal of hypertension · 2021Article
- Data mining in clinical big data: the frequently used databases, steps, and methodological models.Military Medical Research · 2021Review
- Using a risk model for probability of cancer in pulmonary nodules.Thoracic cancer · 2021Article
- Using data mining techniques to fight and control epidemics: A scoping review.Health and technology · 2021Article
- Different Data Mining Approaches Based Medical Text Data.Journal of healthcare engineering · 2021Review
- Article
- Prediction of Suicidal Ideation among Korean Adults Using Machine Learning: A Cross-Sectional Study.Psychiatry investigation · 2020Article
- Can Artificial Intelligence Improve the Management of Pneumonia.Journal of clinical medicine · 2020Review
- Imaging Examination and Quantitative Detection and Analysis of Gastrointestinal Diseases Based on Data Mining Technology.Journal of medical systems · 2019Article
- TRANSLATOR Database-A Vision for a Multi-Institutional Research Network.Topics in companion animal medicine · 2019Article
- Optimization of Electronic Medical Records for Data Mining Using a Common Data Model.Topics in companion animal medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo review theories and technologies of big data mining and their application in clinical medicine. DATA SOURCES: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. STUDY SELECTION: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected.
resultsThis review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine.
conclusionBig data mining has the potential to play an important role in clinical medicine.
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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.