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data mining
Sign in to saveAlso known as data discovery, datamining, knowledge discovery, information mining, mining of data, mining data
the process of extracting and discovering patterns in large data sets
Data mining is the process of searching through large collections of information to find hidden patterns and meaningful connections that might not be obvious at first glance. It matters because these discovered patterns can help businesses, researchers, and organizations make better decisions and understand trends in everything from customer behavior to scientific research.
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Research
48,772 papers- Data mining in clinical big data: the frequently used databases, steps, and methodological models.ReviewMilitary Medical Research · 2021Wu WT, Li YJ, Feng AZ et al.DOI: 10.1186/s40779-021-00338-z
- Clinical data mining: challenges, opportunities, and recommendations for translational applications.ReviewJournal of translational medicine · 2024Qiao H, Chen Y, Qian C et al.DOI: 10.1186/s12967-024-05005-0
- Different Data Mining Approaches Based Medical Text Data.ReviewJournal of healthcare engineering · 2021Xiao W, Jing L, Xu Y et al.DOI: 10.1155/2021/1285167
- Editorial--Data mining in bioinformatics.Journal of bioinformatics and computational biology · 2015Zhao XMDOI: 10.1142/S0219720015020047
- Process mining and data mining applications in the domain of chronic diseases: A systematic review.Artificial intelligence in medicine · 2023Chen K, Abtahi F, Carrero JJ et al.DOI: 10.1016/j.artmed.2023.102645
- The role of data science in healthcare advancements: applications, benefits, and future prospects.ReviewIrish journal of medical science · 2022Subrahmanya SVG, Shetty DK, Patil V et al.DOI: 10.1007/s11845-021-02730-z
- Data mining and machine learning in HIV infection risk research: An overview and recommendations.ReviewArtificial intelligence in medicine · 2024Ge Q, Lu X, Jiang R et al.DOI: 10.1016/j.artmed.2024.102887
- Data mining and machine learning in cancer survival research: An overview and future recommendations.ReviewJournal of biomedical informatics · 2022Kaur I, Doja MN, Ahmad TDOI: 10.1016/j.jbi.2022.104026
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Article
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.
The term "data mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself. It also is a buzzword and is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support systems, including artificial intelligence (e.g., machine learning) and business intelligence. Often the more general terms (large scale) data analysis and analytics—or, when referring to actual methods, artificial intelligence and machine learning—are more appropriate.
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