一个易于解释的规则,涉及多种形式的对对分子比较,用于乳腺癌管理的临床决策
Xin Huang1, Jingyu Chen2, Xinyu He3
1School of Artificial Intelligence, Anshan Normal University, Anshan, Liaoning, China; Biomedical Engineering Postdoctoral Research Station, Dalian University of Technology, Dalian, Liaoning, China; Postdoctoral Workstation of Dalian Yongjia Electronic Technology Co., Ltd, Dalian, Liaoning, China.
Journal of pharmaceutical and biomedical analysis
|January 10, 2026
概括
一个名为RI-MFR的新算法识别了乳腺癌 (BC) 发展和治疗中的关键分子参与者. 这种可解释的方法可以改善早期检测和个性化治疗,以更好地管理BC.
科学领域:
- 生物化学 生物化学
- 基因组学就是基因组学.
- 代谢学 代谢学 代谢学
- 计算生物学 计算生物学
背景情况:
- 乳腺癌 (BC) 转移是女性癌症死亡的主要原因,需要改进早期检测和治疗策略.
- 当前复杂的分类算法缺乏生物解释性,阻碍了个性化治疗方法和了解疾病进展.
- 简单的,可解释的算法对于通过提供生物见解和促进定制治疗来推进BC管理至关重要.
研究的目的:
- 为BC临床管理引入一种新的,可解释的决策规则算法,RI-MFR (与多种关系形式的关系推理).
- 开发一种全面分析分子关系的方法,用于从高维数据中识别关键生物标志物.
- 提供对BC发育和治疗反应的生物学可解释的见解.
主要方法:
- 开发了RI-MFR,这是一种使用联合概率质量函数进行线性和非线性对对分子比较的新算法.
- 应用RI-MFR分析BC发育的基因组学数据集和治疗前后变化的代谢概况.
- 根据所选的分子对推断出准确,可解释的决策规则,以了解分类机制并减少样本变化效应.
主要成果:
- RI-MFR成功地确定了参与葡萄糖脂代谢的基因和代谢物,作为BC发育的关键因素.
- 算法表明,这些因素有助于提高BC治疗的有效性.
- 与其他算法相比,RI-MFR取得了明显更好的分类结果 (p < 0.05),突出了其实用性.
结论:
- RI-MFR是一种有价值和可解释的工具,用于在临床BC管理中识别关键的生物信息.
- 这些发现表明,糖脂代谢在BC进展和治疗反应中起着重要作用.
- 算法的提供生物洞察力的能力促进了针对乳腺癌的个性化医疗方法.
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