• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Scope, design, and reporting of prediction models for antineoplastic drugs-related adverse drug events: A systematic review of machine learning and traditional modeling.

作者信息

Jiang Dan, Song Zaiwei, Hu Yang, Li Xinya, Zhao Rongsheng

机构信息

Department of Pharmacy, Peking University Third Hospital, Beijing, China.

Institute for Drug Evaluation, Peking University Health Science Center, Beijing, China.

出版信息

J Evid Based Med. 2023 Dec;16(4):420-423. doi: 10.1111/jebm.12558. Epub 2023 Oct 20.

DOI:10.1111/jebm.12558
PMID:37862271
Abstract
摘要

相似文献

1
Scope, design, and reporting of prediction models for antineoplastic drugs-related adverse drug events: A systematic review of machine learning and traditional modeling.抗肿瘤药物相关不良药物事件预测模型的范围、设计与报告：机器学习与传统建模的系统评价
J Evid Based Med. 2023 Dec;16(4):420-423. doi: 10.1111/jebm.12558. Epub 2023 Oct 20.
2
Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?机器学习在临床质量保证中的应用跟踪：我们能否在肿瘤学试验中检测到不良事件报告不足的情况？
Drug Saf. 2020 Mar;43(3):295-296. doi: 10.1007/s40264-019-00894-3.
3
Machine learning prediction of side effects for drugs in clinical trials.机器学习预测临床试验中药物的副作用。
Cell Rep Methods. 2022 Dec 7;2(12):100358. doi: 10.1016/j.crmeth.2022.100358. eCollection 2022 Dec 19.
4
Machine-learning-based adverse drug event prediction from observational health data: A review.基于机器学习的观察性健康数据中药物不良事件预测：综述。
Drug Discov Today. 2023 Sep;28(9):103715. doi: 10.1016/j.drudis.2023.103715. Epub 2023 Jul 17.
5
Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles.从肿瘤学全文文章中大规模自动提取与靶向抗癌药物相关的副作用
J Biomed Inform. 2015 Jun;55:64-72. doi: 10.1016/j.jbi.2015.03.009. Epub 2015 Mar 27.
6
The Next Generation of Machine Learning in DDIs Prediction.新一代药物相互作用预测中的机器学习。
Curr Pharm Des. 2021;27(23):2728-2736. doi: 10.2174/1381612827666210127122312.
7
Applications of Machine Learning Methods in Drug Toxicity Prediction.机器学习方法在药物毒性预测中的应用。
Curr Top Med Chem. 2018;18(12):987-997. doi: 10.2174/1568026618666180727152557.
8
Machine learning to predict adverse drug events based on electronic health records: a systematic review and meta-analysis.基于电子健康记录的机器学习预测药物不良事件：系统评价与荟萃分析
J Int Med Res. 2024 Dec;52(12):3000605241302304. doi: 10.1177/03000605241302304.
9
Assessing Drug Development Risk Using Big Data and Machine Learning.利用大数据和机器学习评估药物研发风险。
Cancer Res. 2021 Feb 15;81(4):816-819. doi: 10.1158/0008-5472.CAN-20-0866. Epub 2020 Dec 22.
10
Machine learning on adverse drug reactions for pharmacovigilance.药物警戒中的药物不良反应机器学习。
Drug Discov Today. 2019 Jul;24(7):1332-1343. doi: 10.1016/j.drudis.2019.03.003. Epub 2019 Mar 12.

引用本文的文献

1
Immune checkpoint inhibitors-related thyroid dysfunction: influencing factor analysis, prediction model development, and management strategy proposal.免疫检查点抑制剂相关甲状腺功能障碍：影响因素分析、预测模型建立及管理策略建议。
Cancer Immunol Immunother. 2024 Nov 2;74(1):2. doi: 10.1007/s00262-024-03816-0.