ReviewInternational neurourology journal2014
Big data analysis using modern statistical and machine learning methods in medicine.
Review in International neurourology journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Modeling interrelationships between health behaviors in overweight breast cancer survivors: Applying Bayesian networks.PloS one · 2018Trial
- Data-Driven Printability Modeling of Hydrogels for Precise Direct Ink Writing Based on Rheological Properties.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Predicting the effects of temperature variability on nutritional status of children under five in Sub-Saharan Africa using machine learning.Scientific reports · 2026Article
- Deferoxamine addresses metabolic dysregulation and urinary tract infections in weight-associated gestational diabetes mellitus.European journal of medical research · 2025Article
- Identification of Bone Metastasis-Related Gene Networks in Lung Cancer: Implications for Bone Metabolism.Journal of bone metabolism · 2025Article
- Vowel segmentation impact on machine learning classification for chronic obstructive pulmonary disease.Scientific reports · 2025Observational
- Probabilistic graphical modelling using Bayesian networks for predicting clinical outcome after posterior decompression in patients with degenerative cervical myelopathy.Annals of medicine · 2023Article
- Article
- Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study.Heliyon · 2022Article
- GLIMPSE: a glioblastoma prognostication model using ensemble learning-a surveillance, epidemiology, and end results study.Health information science and systems · 2021Article
- Google Trends application for the study of information search behaviour on oropharyngeal cancer in Spain.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2021Article
- Multiplicative Holts Winter Model for Trend Analysis and Forecasting of COVID-19 Spread in India.SN computer science · 2021Article
- Machine Learning-Based DNA Methylation Score for Fetal Exposure to Maternal Smoking: Development and Validation in Samples Collected from Adolescents and Adults.Environmental health perspectives · 2020Article
- Big data analytics for preventive medicine.Neural computing & applications · 2020Article
- PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data.Sensors (Basel, Switzerland) · 2019Article
- Peripheral transcriptomic biomarkers for early detection of sporadic Alzheimer disease?Dialogues in clinical neuroscience · 2018Review
- A Convenient Non-harm Cervical Spondylosis Intelligent Identity method based on Machine Learning.Scientific reports · 2018Article
- Causal Inference Network of Genes Related with Bone Metastasis of Breast Cancer and Osteoblasts Using Causal Bayesian Networks.Journal of bone metabolism · 2018Article
- Information-Based Medicine in Glioma Patients: A Clinical Perspective.Computational and mathematical methods in medicine · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease.
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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.