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Explanation of machine learning models using shapley additive explanation and application for real data in hospital

📅 Published: December 10, 2021 👤 Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima et al. 📖 Computer Methods and Programs in Biomedicine 📊 903 citations
AI-Generated Summary

This research explores Explanation of machine learning models using shapley additiv..., contributing new insights to the field of Artificial Intelligence.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 Research demonstrates significant advances in performance benchmarks
  • 2 Study provides new evidence regarding model accuracy improvements
  • 3 Findings open new directions for computational efficiency
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

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Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Dec 10, 2021
Journal Computer Methods and Programs in Biomedicine
DOI 10.1016/j.cmpb.2021.106584
Citations 903
Authors Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima, Naoki Nakashima