ReviewHealth care science2023
Challenges and opportunities of big data analytics in healthcare.
Review in Health care science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 6 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
6 citing papers in PubMed.
- Article
- Assessing the accuracy and educational value of ChatGPT-generated content for core topics in cardiology: a descriptive analysis at Selçuk University Cardiology Clinic.BMC medical education · 2026Article
- Exploring the integration of medical and preventive chronic disease health management in the context of big data.Frontiers in public health · 2025Review
- Article
- Development and validation of a spontaneous preterm birth risk prediction algorithm based on maternal bioinformatics: A single-center retrospective study.BMC pregnancy and childbirth · 2024Article
- Challenges and opportunities of big data analytics in healthcare.Health care science · 2023Review
Corrections and comments
- Retracted
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data science is an interdisciplinary discipline that employs big data, machine learning algorithms, data mining techniques, and scientific methodologies to extract insights and information from massive amounts of structured and unstructured data. The healthcare industry constantly creates large, important databases on patient demographics, treatment plans, results of medical exams, insurance coverage, and more. The data that IoT (Internet of Things) devices collect is of interest to data scientists. Data science can help with the healthcare industry's massive amounts of disparate, structured, and unstructured data by processing, managing, analyzing, and integrating it. To get reliable findings from this data, proper management and analysis are essential. This article provides a comprehensive study and discussion of process data analysis as it pertains to healthcare applications. The article discusses the advantages and disadvantages of using big data analytics (BDA) in the medical industry. The insights offered by BDA, which can also aid in making strategic decisions, can assist the healthcare system.
Indexed as
Identifiers
What OpenQuestion holds
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.