• 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

Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations.

作者信息

Chen Jonathan H, Asch Steven M

机构信息

From the Department of Medicine, Stanford University, Stanford (J.H.C., S.M.A.), and the Center for Innovation to Implementation (Ci2i), Veteran Affairs Palo Alto Health Care System, Palo Alto (S.M.A.) - both in California.

出版信息

N Engl J Med. 2017 Jun 29;376(26):2507-2509. doi: 10.1056/NEJMp1702071.

DOI:10.1056/NEJMp1702071
PMID:28657867
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5953825/
Abstract
摘要

相似文献

1
Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations.医学中的机器学习与预测——超越过高期望的顶峰
N Engl J Med. 2017 Jun 29;376(26):2507-2509. doi: 10.1056/NEJMp1702071.
2
PCA-based polling strategy in machine learning framework for coronary artery disease risk assessment in intravascular ultrasound: A link between carotid and coronary grayscale plaque morphology.基于主成分分析的机器学习框架中的投票策略用于血管内超声冠状动脉疾病风险评估：颈动脉与冠状动脉灰度斑块形态之间的联系
Comput Methods Programs Biomed. 2016 May;128:137-58. doi: 10.1016/j.cmpb.2016.02.004. Epub 2016 Mar 2.
3
Prostate Cancer Probability Prediction By Machine Learning Technique.基于机器学习技术的前列腺癌概率预测
Cancer Invest. 2017 Nov 26;35(10):647-651. doi: 10.1080/07357907.2017.1406496.
4
Machine Learning Principles Can Improve Hip Fracture Prediction.机器学习原理可改善髋部骨折预测。
Calcif Tissue Int. 2017 Apr;100(4):348-360. doi: 10.1007/s00223-017-0238-7. Epub 2017 Feb 14.
5
Improve Glioblastoma Multiforme Prognosis Prediction by Using Feature Selection and Multiple Kernel Learning.通过特征选择和多核学习改善多形性胶质母细胞瘤预后预测
IEEE/ACM Trans Comput Biol Bioinform. 2016 Sep-Oct;13(5):825-835. doi: 10.1109/TCBB.2016.2551745. Epub 2016 Apr 7.
6
Machine Learning in Medicine.医学中的机器学习
Circulation. 2015 Nov 17;132(20):1920-30. doi: 10.1161/CIRCULATIONAHA.115.001593.
7
Using Machine Learning to Define the Association between Cardiorespiratory Fitness and All-Cause Mortality (from the Henry Ford Exercise Testing Project).利用机器学习确定心肺适能与全因死亡率之间的关联（来自亨利·福特运动测试项目）。
Am J Cardiol. 2017 Dec 1;120(11):2078-2084. doi: 10.1016/j.amjcard.2017.08.029. Epub 2017 Aug 30.
8
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.预测未来——大数据、机器学习与临床医学。
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
9
Big Data and Predictive Analytics: Recalibrating Expectations.大数据与预测分析：重新校准期望
JAMA. 2018 Jul 3;320(1):27-28. doi: 10.1001/jama.2018.5602.
10
Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.基于机器学习算法的移植后 100 天异基因造血干细胞移植死亡率预测：欧洲血液和骨髓移植协会急性白血病工作组回顾性数据挖掘研究。
J Clin Oncol. 2015 Oct 1;33(28):3144-51. doi: 10.1200/JCO.2014.59.1339. Epub 2015 Aug 3.

引用本文的文献

1
Artificial Intelligence and Its Impact on the Management of Lumbar Degenerative Pathology: A Narrative Review.人工智能及其对腰椎退行性病变管理的影响：一项叙述性综述
Medicina (Kaunas). 2025 Aug 1;61(8):1400. doi: 10.3390/medicina61081400.
2
Development and Validation of an Artificial Intelligence-Driven Model for Accurate Classification of Erythrodermic Psoriasis Severity: Erythrodermic Psoriasis Integrated Classification System (EPICS).人工智能驱动的红皮病型银屑病严重程度准确分类模型的开发与验证：红皮病型银屑病综合分类系统（EPICS）
Am J Clin Dermatol. 2025 Aug 26. doi: 10.1007/s40257-025-00980-6.
3
Unveiling the hidden burden of COVID-19 in Brazil's obstetric population with severe acute respiratory syndrome: A machine learning model.利用机器学习模型揭示巴西患有严重急性呼吸综合征的产科人群中新冠病毒病的隐性负担
PLoS One. 2025 Aug 22;20(8):e0330375. doi: 10.1371/journal.pone.0330375. eCollection 2025.
4
Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.优化阿尔茨海默病血浆生物标志物的检测时机及成本效益应用。
Alzheimers Res Ther. 2025 Aug 20;17(1):194. doi: 10.1186/s13195-025-01851-2.
5
An Interpretable Machine Learning Model for Predicting Early Neurological Deterioration Following Posttraumatic Acute Diffuse Brain Swelling.一种用于预测创伤后急性弥漫性脑肿胀后早期神经功能恶化的可解释机器学习模型。
Neurocrit Care. 2025 Aug 11. doi: 10.1007/s12028-025-02340-y.
6
Machine learning prediction of early reoperation following lower extremity tumor resection and endoprosthetic reconstruction: A PARITY trial secondary analysis.下肢肿瘤切除及人工关节置换重建术后早期再次手术的机器学习预测：PARITY试验的二次分析
J Orthop Surg Res. 2025 Aug 4;20(1):727. doi: 10.1186/s13018-025-06139-7.
7
Understanding Clinician Perceptions of GenAI: A Mixed Methods Analysis of Clinical Documentation Tasks.了解临床医生对生成式人工智能的看法：临床文档任务的混合方法分析
J Med Syst. 2025 Aug 2;49(1):101. doi: 10.1007/s10916-025-02234-8.
8
Bridging the Regulatory Divide: A Dual-Pathway Framework Using SRA Approvals and AI Evaluation to Ensure Drug Quality in Developing Countries.弥合监管差距：一种利用SRA批准和人工智能评估的双路径框架，以确保发展中国家的药品质量。
Pharmaceuticals (Basel). 2025 Jul 10;18(7):1024. doi: 10.3390/ph18071024.
9
Disparities in clinical trial enrollment related to laser interstitial thermal therapy for central nervous system metastases.与激光间质热疗治疗中枢神经系统转移瘤相关的临床试验入组差异。
Neurosurg Rev. 2025 Jul 22;48(1):575. doi: 10.1007/s10143-025-03733-5.
10
Development and validation of an interpretable machine learning model for predicting Gleason score upgrade in prostate cancer.用于预测前列腺癌Gleason评分升级的可解释机器学习模型的开发与验证
Transl Androl Urol. 2025 Jun 30;14(6):1631-1644. doi: 10.21037/tau-2025-178. Epub 2025 Jun 26.

本文引用的文献

1
Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.临床数据对数据驱动的住院临床医嘱集未来决策的相关性正在衰减。
Int J Med Inform. 2017 Jun;102:71-79. doi: 10.1016/j.ijmedinf.2017.03.006. Epub 2017 Mar 18.
2
Piloting electronic medical record-based early detection of inpatient deterioration in community hospitals.在社区医院试点基于电子病历的住院患者病情恶化早期检测。
J Hosp Med. 2016 Nov;11 Suppl 1(Suppl 1):S18-S24. doi: 10.1002/jhm.2652.
3
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.预测未来——大数据、机器学习与临床医学。
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
4
Big data. The parable of Google Flu: traps in big data analysis.大数据。谷歌流感预测的教训：大数据分析中的陷阱。
Science. 2014 Mar 14;343(6176):1203-5. doi: 10.1126/science.1248506.