Creation and assessment of claims-based algorithms for detecting interstitial lung disease in Japanese cancer patients utilizing real-world data in standard clinical settings
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By
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Yu-Jing Huang
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Toshihiro Takeda
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Yoshie Shimai
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Taizo Murata
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Kento Sugimoto
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Yoshito Takeda
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Haruhiko Hirata
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Makoto Yamamoto
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Midori Yoneda
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Seigo Minami
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Masahiro Higashi
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Alan James Michael Brnabic
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Zbigniew Kadziola
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Tsutomu Kawaguchi
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Yucherng Chen
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Yasushi Matsumura
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September 9, 2026
3 Topic Commentaries
Intracranial Hemorrhages, Central Nervous System Infections, Machine Learning
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Dr. Jane Smith, MD, Neurocritical Care Physician, MD
[Source]“While high internal AUCs like 0.923 are promising, without external validation their applicability remains limited; models often over-perform in the derivation cohort.”
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Dr. Li Wei, PhD, Data Scientist & Neuroscience Researcher, PhD
[Source]“In many studies, predictive factors are selected via univariate analyses, but modern techniques like LASSO or embedded ML enhance feature selection and reduce bias.”
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Dr. Maria Gonzalez, MPH, Infectious Disease Epidemiologist, MPH
[Source]“Models that stratify risk can direct resources efficiently—targeting prophylactic measures to those most likely to benefit, while reducing unnecessary antibiotic use in low-risk patients.”
