CME Exam 2: Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records

首页> 外文期刊>Gastroenterology >CME Exam 2: Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records

【24h】

CME Exam 2: Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records

机译：CME 考试 2：使用电子健康记录的机器学习预测食管或胃贲门腺癌的新发

获取原文

获取原文并翻译 | 示例

开具论文收录证明 >>

AI期刊论文写作 >>

页面导航

摘要
著录项
引文网络
相似文献
相关主题

摘要

The Kunzmann and Nord-Tr?ndelag Health Study (HUNT) tools have previously been validated for identifying neoplastic Barrett’s esophagus and predicting adenocarcinomas of the esophagus or gastric cardia.

机译：Kunzmann 和 Nord-Tr？ndelag 健康研究（HUNT）工具先前已被验证可用于识别肿瘤性 Barrett 食管和预测食管或胃贲门腺癌。

著录项

来源
《Gastroenterology》 |2023年第6期|e11-e11|共1页
作者

展开▼
作者单位

展开▼
收录信息
原文格式 PDF
正文语种英语
中图分类消化系及腹部疾病;
关键词

相似文献

外文文献
中文文献
专利

1. Development and validation of a machine learning model using electronic health records to predict trauma- and stressor-related psychiatric disorders after hospitalization with sepsis [J] . Papini Santiago, Iturralde Esti, Lu YunGreene John D.Barreda FernandoSterling Stacy A.Liu Vincent X. translational psychiatry . 2023,第1期

机译：开发和验证使用电子健康记录的机器学习模型，以预测脓毒症住院后与创伤和应激源相关的精神疾病
2. Data on Machine Learning Reported by Rui Fa and Colleagues (Early prediction of in-hospital mortality utilizing multivariate predictive modelling of electronic medical records and socio-determinants of health of the first day of hospitalization) [J] . Robotics & Machine Learning Daily News . 2023,第28期

机译：Rui Fa 及其同事报告的机器学习数据（利用电子病历和住院第一天健康的社会决定因素的多变量预测模型对住院死亡率进行早期预测）
3. Correction to: A hybrid machine learning framework to predict mortality in paralytic ileus patients using electronic health records (EHRs) [J] . Fahad Shabbir Ahmed, Liaqat Ali, Raza Ul MustafaHasan Ali KhattakTahir HameedIram WajahatSeifedine KadrySyed Ahmad Chan Bukhari Journal of ambient intelligence and humanized computing . 2023,第10期

机译：更正：使用电子健康记录（EHR）预测麻痹性肠梗阻患者死亡率的混合机器学习框架
4. Using Electronic Health Records and Machine Learning to Predict Postpartum ' Depression [C] . Shuojia Wang, Jyotishman Pathak, Yiye Zhang MEDINFO . 2019

机译：使用电子健康记录和机器学习预测产后的抑郁症
5. Predicting Drug Misuse Status Using Machine Learning on Electronic Health Records [D] . Kania, Robert. 2020

机译：使用机器学习在电子健康记录上预测药物滥用状态
6. Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data [O] . Divneet Mandair, Premanand Tiwari, Steven Simon, 2020

机译：采用机器学习预测事件心肌梗死应用于协调电子健康记录数据
7. Data Leakage in Health Outcomes Prediction With Machine Learning. Comment on “Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning” [O] . Alexandre Chiavegatto Filho, André Filipe De Moraes Batista, Hellen Geremias dos Santos 2021

机译：与机器学习的健康结果预测数据泄漏。评论“明年内发生的事故高压措施：使用全州电子健康记录和机器学习的前瞻性研究”
8. Framework for Smart Electronic Health Record- Linked Predictive Models to Optimize Care for Complex Digestive Diseases. [R] . Betteridge, J. D. 2015

机译：智能电子健康记录链接预测模型的框架，以优化复杂消化疾病的护理。

CME Exam 2: Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records

摘要

著录项

引文网络

相似文献

相关主题

期刊订阅