通过文献文本挖掘扩大癌症治疗复杂性的边界
Danna Niezni1, Hillel Taub-Tabib2, Yuval Harris1
1Faculty of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa, Israel.
Artificial intelligence in medicine
|November 4, 2023
概括
开发最佳的癌症药物组合是复杂的. 一个新的文本挖掘工具,Plan Builder,加速了高复杂性组合治疗 (HCCT) 的创建,提高了研究人员的速度和质量.
科学领域:
- 在瘤学瘤学.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 药物联合治疗对于癌症治疗至关重要.
- 使用4种以上药物开发高复杂性联合治疗 (HCCT) 面临着组合性挑战.
- 现有的HCCT规划方法耗时且复杂.
研究的目的:
- 为了解决当前组合疗法开发中的局限性.
- 引入基于文本挖掘 (TM) 的工具Plan Builder (PB),以实现高效的HCCT生成.
- 评估PB在加速HCCT计划开发方面的有效性.
主要方法:
- 文献审查以确定组合治疗的局限性.
- 开发了使用文本挖掘的Plan Builder (PB) 工具.
- 与传统方法相比,评估PB在生成HCCT计划方面的表现.
主要成果:
- PB显著提高了HCCT计划创建的速度和质量.
- 研究人员和专家证明使用PB提高了效率.
- 该工具有效地克服了HCCT中的组合式爆炸挑战.
结论:
- 计划构建器 (PB) 工具加速了高复杂性组合治疗 (HCCT) 的开发.
- PB促进了对药物组合策略的现有文献的更有效利用.
- 发布PB旨在赋予研究人员在HCCT规划和临床疗效证明方面的权力.
关键词:
组合疗法是一种联合疗法.众包服务 (crowdsourcing) 是一种众包服务.药物协同作用 药物协同作用基于文献的发现发现.个性化治疗是个性化的治疗.文本挖掘 (Text Mining) 是一种文字挖掘方式.更多相关视频
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