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June 19, 2026Annals of Vascular DiseasesOpen Access

Machine Learning Is Not Just for Prediction: Its Role as an Exploratory Analytical Tool in Medicine

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SKSei Komatsu

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Overview

Review discusses exploratory machine learning's role in generating hypotheses from complex medical data.

Key Points

  • The review aims to differentiate between predictive and exploratory machine learning, emphasizing its potential for hypothesis generation.
  • Discusses methods including unsupervised learning, interpretable supervised learning, and network analysis.
  • Examines the limitations of conventional hypothesis-driven statistics under certain data conditions.
  • Highlights the need for evaluating exploratory ML based on stability, reproducibility, and interpretability.
  • Exploratory ML is essential for analyzing high-dimensional data and small sample sizes in medical research.
  • Calls for a shift in evaluation criteria for exploratory analyses, focusing on interpretability rather than predictive accuracy.
  • Suggests that integrating exploratory ML may enhance study designs and improve data interpretation in medicine.

Cite This Study

Sei Komatsu (2026) studied this question.

synapsesocial.com/papers/6a34dc5265a5b0777af2ca09https://doi.org/10.3400/avd.ra.26-00055
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