用于预测罕见临床结果的机器学习——大海捞针 - Suppr

Suppr

超能文献

Machine Learning for Predicting Rare Clinical Outcomes-Finding Needles in a Haystack.

作者信息

Wang Fei

机构信息

Weill Cornell Medical College, New York, New York.

出版信息

JAMA Netw Open. 2021 May 3;4(5):e2110738. doi: 10.1001/jamanetworkopen.2021.10738.

DOI:10.1001/jamanetworkopen.2021.10738

PMID:34019091

Abstract

摘要

相似文献

Machine Learning for Predicting Rare Clinical Outcomes-Finding Needles in a Haystack.用于预测罕见临床结果的机器学习——大海捞针

JAMA Netw Open. 2021 May 3;4(5):e2110738. doi: 10.1001/jamanetworkopen.2021.10738.

Finding Needles in a Haystack: Determining Key Molecular Descriptors Associated with the Blood-brain Barrier Entry of Chemical Compounds Using Machine Learning.在干草堆中找针：使用机器学习确定与化学化合物血脑屏障进入相关的关键分子描述符。

Mol Inform. 2019 Aug;38(8-9):e1800164. doi: 10.1002/minf.201800164. Epub 2019 Jul 19.

[Using Machine Learning to Investigate Factors Influencing the Efficacy of "Shoulder Tri-needles Therapy" in Treatment of Shoulder-hand Syndrome in 586 Stroke Patients].

Zhen Ci Yan Jiu. 2018 Nov 25;43(11):733-7. doi: 10.13702/j.1000-0607.170231.

Investigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms.运用机器学习算法探究脑深部电刺激手术的风险因素并预测其并发症

World Neurosurg. 2020 Feb;134:e325-e338. doi: 10.1016/j.wneu.2019.10.063. Epub 2019 Oct 18.

Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists.在高维干草堆中寻找针：神经科学家的典型相关分析。

Neuroimage. 2020 Aug 1;216:116745. doi: 10.1016/j.neuroimage.2020.116745. Epub 2020 Apr 8.

Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.机器学习准确预测踝关节骨折切开复位内固定术后的短期预后。

J Foot Ankle Surg. 2019 May;58(3):410-416. doi: 10.1053/j.jfas.2018.09.004. Epub 2019 Feb 23.

Computerized seizure detection on ambulatory EEG: Finding the needles in the haystack.动态脑电图的计算机化癫痫检测：大海捞针。

Neurology. 2019 Apr 2;92(14):641-642. doi: 10.1212/WNL.0000000000007222. Epub 2019 Mar 6.

Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.超越多药耐药性：利用机器和统计学习模型在结核分枝杆菌耐药性预测中的罕见变异。

EBioMedicine. 2019 May;43:356-369. doi: 10.1016/j.ebiom.2019.04.016. Epub 2019 Apr 29.

Applying machine learning to predict real-world individual treatment effects: insights from a virtual patient cohort.应用机器学习预测真实世界的个体治疗效果：来自虚拟患者队列的见解。

J Am Med Inform Assoc. 2019 Oct 1;26(10):977-988. doi: 10.1093/jamia/ocz036.

Chasing Therapeutic Targets in Thymic Malignancies: Finding Needles in the Haystack to Frame a Comprehensive Canvas?胸腺恶性肿瘤治疗靶点的探索：大海捞针以勾勒全面图景？

J Thorac Oncol. 2016 Aug;11(8):1197-1200. doi: 10.1016/j.jtho.2016.06.007.

引用本文的文献

Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.基于生物信息学和机器学习的缺血性卒中糖基化相关基因的鉴定与验证

J Mol Neurosci. 2025 Apr 29;75(2):60. doi: 10.1007/s12031-025-02352-5.

Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities.基于白质高信号MRI影像组学的急性缺血性脑卒中功能预后机器学习预测模型

BMC Med Imaging. 2025 Mar 19;25(1):91. doi: 10.1186/s12880-025-01632-1.

Predicting Mechanical Thrombectomy Outcome and Time Limit through ADC Value Analysis: A Comprehensive Clinical and Simulation Study Using Machine Learning.通过表观扩散系数（ADC）值分析预测机械取栓结果及时间限制：一项使用机器学习的综合临床与模拟研究

Diagnostics (Basel). 2023 Jun 21;13(13):2138. doi: 10.3390/diagnostics13132138.

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.多模态深度学习在急诊科 COVID-19 预后预测中的应用：一项双中心研究。

Sci Rep. 2023 Jul 5;13(1):10868. doi: 10.1038/s41598-023-37512-3.

Association between SYVN1 and SEL1 genetic polymorphisms and remission in rheumatoid arthritis patients treated with TNF-α inhibitors: a machine learning approach.SYVN1 和 SEL1 基因多态性与 TNF-α 抑制剂治疗的类风湿关节炎患者缓解的相关性：一种机器学习方法。

Immunol Res. 2023 Oct;71(5):709-716. doi: 10.1007/s12026-023-09382-4. Epub 2023 Apr 29.

Small vessel disease burden predicts functional outcomes in patients with acute ischemic stroke using machine learning.机器学习在急性缺血性脑卒中患者中预测小血管疾病负担与功能结局的关系。

CNS Neurosci Ther. 2023 Apr;29(4):1024-1033. doi: 10.1111/cns.14071. Epub 2023 Jan 17.

Building the Model.建立模型。

Arch Pathol Lab Med. 2023 Jul 1;147(7):826-836. doi: 10.5858/arpa.2021-0635-RA.

Quickly identifying people at risk of opioid use disorder in emergency departments: trade-offs between a machine learning approach and a simple EHR flag strategy.快速识别急诊科中阿片类药物使用障碍风险人群：机器学习方法与简单电子健康记录标记策略之间的权衡。

BMJ Open. 2022 Sep 14;12(9):e059414. doi: 10.1136/bmjopen-2021-059414.

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