The XGBoost-based approach demonstrated robust external validation across multiple centers, supporting clinical adoption to guide personalized treatment decisions.

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

A machine learning-based model can predict 30-day in-hospital mortality among patients with asthma in the ICU.

The conversion of carbon dioxide into clean fuels is regarded as an important route toward carbon neutrality. CO2 methanation ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional ...

本研究针对短读长测序数据中结构变异(SV)检测精度不足的问题，开发了SV-MeCa元调用系统。通过整合BreakDancer等7种SV检测工具，结合XGBoost机器学习算法，显著提高了插入(DEL)和缺失(INS)变异的检测准确率(F1值达0.58-0.42)。该研究为临床基因组分析提供了更可靠的SV ...

The core of big data models lies in the synergy of algorithm innovation, computational power support, and data governance to ...

Social media has birthed an entire lexicon replicated by millions online — even if these words don’t actually mean skibidi. On today’s show, we talk to author Adam Aleksic about how TikTok and ...