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「AI合成データが医療経済評価を変える日は来るか」の検索結果

4 件中 4 件を表示 (4233 ms) · ⭐ 保存した論文

AI が生成した英語クエリを見る 
("artificial intelligence"[MeSH] OR "AI" OR "machine learning"[MeSH]) AND ("synthetic data" OR "simulated data" OR "generated data") AND ("cost-benefit analysis"[MeSH] OR "health care economics"[MeSH] OR "economic evaluation" OR "pharmacoeconomics"[MeSH])

💡 AI/機械学習、合成データ、医療経済評価の3要素をMeSH用語と自由語で組み合わせ、ORで同義語を拡張しました

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🔍 PubMed の検索結果

  • A roadmap for applying machine learning when working with privacy-sensitive data: predicting non-response to treatment for eating disorders.

    Vegard G Svendsen, Ben F M Wijnen, Jan Alexander De Vos 他 · Expert review of pharmacoeconomics & outcomes research · 2023

    Applying machine-learning methodology to clinical data could present a promising avenue for predicting outcomes in patients receiving treatment for psychiatric disorders. However, preserving privacy when working with patient data remains a critical concern. In showcasing how machine-learning can be used to build a clinically relevant prediction model on clinical data, we apply two commonly used ma…

    📄 PubMed で読む (PMID: 37366051)

  • Cost-Effective Fish Volume Estimation in Aquaculture Using Infrared Imaging and Multi-Modal Deep Learning.

    Like Zhang, Yanling Han, Ge Song 他 · Sensors (Basel, Switzerland) · 2026

    Accurate fish volume estimation is essential for sustainable aquaculture management, yet traditional methods are invasive and costly, while existing non-invasive approaches rely on expensive multi-sensor setups. This study proposes a cost-effective infrared (IR)-only pipeline that reconstructs depth and Red Green Blue (RGB) from low-cost infrared videos (<USD 100 per camera), enabling scalable bio…

    📄 PubMed で読む (PMID: 41755162)

  • A Cost-Effective and Scalable Machine Learning Approach for Quality Assessment of Fresh Maize Kernel Using NIR Spectroscopy.

    Jiang Shi, Erkui Yue, Xuejin Zhu 他 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025

    In fresh maize breeding, developing robust and accurate near-infrared (NIR) calibration models traditionally requires significant time, cost, and labor. To address these challenges, a novel machine learning approach is proposed using a Prediction-Correction Neural Network (PCNN) that enables effective modeling from small sample sets augmented with synthetic data based on NIR spectroscopy. For key …

    📄 PubMed で読む (PMID: 41017617)

  • A critical assessment of matching-adjusted indirect comparisons in relation to target populations.

    Ziren Jiang, Jialing Liu, Demissie Alemayehu 他 · Research synthesis methods · 2025

    Matching-adjusted indirect comparison (MAIC) has been increasingly applied in health technology assessments (HTA). By reweighting subjects from a trial with individual participant data (IPD) to match the summary statistics of covariates in another trial with aggregate data (AgD), MAIC enables a comparison of the interventions for the AgD trial population. However, when there are imbalances in effe…

    📄 PubMed で読む (PMID: 41626938)
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