通过文本挖掘对流域区域相关性的机器评估
Philip A Arlen1, Joseph Chakko1, Geoffrey DeGennaro1
1University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL.
Critical reviews in oncogenesis
|April 29, 2024
概括
研究人员创建了一个算法,以找到与佛罗里达州南部相关的癌症临床试验. 该工具通过优先考虑当地癌症需求来解决该地区严重的癌症负担和健康差异.
科学领域:
- 在瘤学瘤学.
- 医疗保健服务研究 医疗服务研究
- 临床试验管理 临床试验管理
背景情况:
- 南佛罗里达州是一个高度多样化的地区,癌症负担和差异很大.
- 迈阿密大学西尔维斯特综合癌症中心为这种复杂的人群提供服务.
- 需要将临床试验与当地社区的具体健康需求相协调.
研究的目的:
- 开发一种工具,用于识别与西尔维斯特综合癌症中心的采集区相关的癌症临床试验.
- 优先考虑针对南佛罗里达州流行癌症和健康差异的试验.
- 改善不同患者群体获得当地相关癌症研究的机会.
主要方法:
- 社区推广与参与办公室开发了一种专门的算法.
- 专注于南佛罗里达州作为采集区,承认其人口和地理多样性.
- 基于局部瘤负担和癌症患病率的优先级策略.
主要成果:
- 一个旨在识别相关临床试验的算法已成功开发.
- 该工具有助于针对南佛罗里达州本地普遍存在的癌症进行试验.
- 这种方法有助于解决西尔维斯特综合癌症中心所服务的人口的具体需求.
结论:
- 开发的算法是协调癌症临床试验与不同地区社区需求的关键资源.
- 优先考虑当地相关的试验对于解决重大癌症负担和差异至关重要.
- 这一举措增强了该中心通过有针对性的研究有效地为其流域提供服务的能力.
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