ArticleJournal of diabetes and metabolic disorders2021
A survey on data mining techniques used in medicine.
Article in Journal of diabetes and metabolic disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Response to venom immunotherapy: Exploratory retrospective machine learning clustering analysis.The journal of allergy and clinical immunology. Global · 2026Article
- Unveiling Epidemiologic Insights: A Case-Control Study of Congenital Cleft Lip and/or Palate Using Association Rule Mining.BioMed research international · 2026Observational
- Logistic regression versus C5.0 decision tree in predicting female stress urinary incontinence risk using clinical and pelvic floor ultrasound data: a model development and validation study.BMC women's health · 2025Article
- Enhancing clinical decision-making in closed pelvic fractures with machine learning models.Biomolecules & biomedicine · 2025Article
- An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis.Scientific reports · 2025Article
- Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review.Frontiers in pharmacology · 2024Review
- Causes of death among United States decedents with ALS: An eye toward delaying mortality.Annals of clinical and translational neurology · 2023Article
- A study on optimization of delayed production mode of iron and steel enterprises based on data mining.PloS one · 2023Article
- Extracting New Temporal Features to Improve the Interpretability of Undiagnosed Type 2 Diabetes Mellitus Prediction Models.Journal of personalized medicine · 2022Article
- Possibility of Multiple Drug-Drug Interactions in Patients Treated with Statins: Analysis of Data from the Japanese Adverse Drug Event Report (JADER) Database and Verification by Animal Experiments.International journal of medical sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data mining is the process of analyzing a massive amount of data to identify meaningful patterns and detect relations, which can lead to future trend prediction and appropriate decision making. Data mining applications are significant in marketing, banking, medicine, etc. In this paper, we present an overview of data mining applications in medicine to provide a clear view of the challenges and previous works in this area for researchers. Data mining techniques such as Decision Tree, Random Forest, K-means Clustering, Support Vector Machine, Logistic Regression, Neural Network, Naive Bayes, and association rule mining are used for diagnosing, prognosis, classifying, constructing predictive models, and analyzing risk factors of various diseases. The main objective of the paper is to analyze and compare different data mining techniques used in the medical applications. We present a summary of the results and provide comparison analysis of the data mining methods employed by the reviewed articles SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40200-021-00884-2.
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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.