彻底改变瘤护理:开创人工智能模型,预测肺炎相关死亡率
Qunzhe Ding1, Yi Zhang2, Zihao Zhang3
1School of Information Management, Wuhan University, Wuhan, Hubei, China.
Frontiers in oncology
|April 3, 2025
概括
肺炎是癌症患者死亡的重要原因之一. 一个新的CatBoost模型准确地预测了生存率,确定手术,阶段,年龄,地点和性别作为关键的预后因素.
科学领域:
- 在瘤学瘤学.
- 传染性疾病 传染性疾病
- 生物统计学 生物统计学
背景情况:
- 肺炎是癌症患者发病和死亡的主要原因,急需准确的预测模型.
- 现有的临床环境缺乏精确的工具来预测肺炎癌症患者的生存结果.
研究的目的:
- 确定肺炎作为癌症患者死亡原因的发病率.
- 分析与癌症患者肺炎相关死亡率相关的趋势和风险因素.
- 开发和验证肺炎癌症患者的生存预测模型.
主要方法:
- 利用了来自监测,流行病学和最终结果 (SEER) 计划的26,938名死于肺炎的癌症患者 (1973-2020年) 的数据.
- 采用考克斯回归分析用于预后因素识别,并开发了CatBoost模型用于生存预测.
- 使用机构队列验证了CatBoost模型,并通过自由访问软件界面部署了它.
主要成果:
- 与肺炎相关的死亡中,前列腺癌,乳腺癌和肺癌最常见. 消化,内分泌,泌尿和血液系统受到影响最多.
- CatBoost模型表现出高预测准确性 (例如,6个月AUC=0.8384) 和在独立数据集上强大的性能.
- 手术,阶段,年龄,部位和性别是关键的预后因素;手术显著影响了不同癌症类型和时间框架的存活率.
结论:
- 肺炎对癌症患者,特别是那些患有消化系统癌症的人来说是一个严重的威胁.
- 早期识别风险因素和及时干预对于改善生活质量和预后至关重要.
- 开发的CatBoost模型为预测存活率和指导临床管理提供了有价值的工具.
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