ArticleMedicine2026
A data portrait-based approach to precision education for medical students in China.
Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Authors and funding
3 authors.
Funding
Abstract
With the rapid development of big data technology, smart campuses from medical universities of China have accumulated a large amount of student behavior data. How to extract hidden and valuable information from a large amount of data has become a problem faced by medical universities of China. This study constructed a framework for the portrait model of medical university students of China, which includes 5 dimensions: identity and organizational data, learning data, economic data, and health and interest data. These data are sourced from the smart campus information system of medical universities of China. Then, K-means clustering method is used to calculate these data, extract the characteristic attributes of students, and construct accurate student data portraits. This study uses big data profiling technology to accurately describe the digital characteristics of students, providing reference for the educational environment of medical universities.
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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.