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Updated: Jan 8, 2026

A High-Throughput Multiplexed Screening for Type 1 Diabetes, Celiac Diseases, and COVID-19
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一个种族敏感的混合框架用于T2D预测,具有可解释的AI和加权合奏

Karlo Abnoosian1, Rahman Farnoosh2, Hamidreza Noushkaran1

  • 1School of Mathematics and Computer Science, Iran University of Science and Technology, Narmak, 1684613114, Tehran, Iran.

Scientific reports
|December 23, 2025
PubMed
概括

一个新的框架改善了早期的2型糖尿病 (T2D) 预测,特别是在资源较少的环境中. 它解决了数据挑战,并确定了特定人群的风险因素,以更好地检测T2D.

关键词:
组合学习学习 组合学习根据FW-CAGIN的推算方法.功能选择 功能选择人口特异性风险的人口特异性风险在SHAP分析中,我们分析了SHAP.预测2型糖尿病的情况

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