Robotics & Machine Learning Daily News2024,Issue(Nov.14) :1-2.

Third Hospital of Hebei Medical University Reports Findings in Heart Failure (Pr edictive modeling of preoperative acute heart failure in older adults with hyper tension: a dual perspective of SHAP values and interaction analysis)

河北医科大学第三医院报告心力衰竭的发现(老年高血压患者术前急性心力衰竭的前瞻性建模:SHAP值和交互分析的双视角)

Robotics & Machine Learning Daily News2024,Issue(Nov.14) :1-2.

Third Hospital of Hebei Medical University Reports Findings in Heart Failure (Pr edictive modeling of preoperative acute heart failure in older adults with hyper tension: a dual perspective of SHAP values and interaction analysis)

河北医科大学第三医院报告心力衰竭的发现(老年高血压患者术前急性心力衰竭的前瞻性建模:SHAP值和交互分析的双视角)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-心脏疾病和疾病的新研究-心力衰竭是心脏疾病研究的主题报告根据《新闻周刊》编辑对河北外报的报道,研究表明:“在老年高血压患者中,髋部骨折伴术前急性心脏衰竭。”失败显著增加手术风险和不良结果,需要及时识别和治疗改善病人结果的管理。本研究旨在提高急性胰腺炎的早期认识老年高血压患者髋部骨折手术前心力衰竭的预测模型应用logistic回归(LR)和机器学习方法优化术前评估和管理。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Heart Disorders and Di seases - Heart Failure is the subject ofa report. According to news reporting o ut of Hebei, People’s Republic of China, by NewsRx editors,research stated, “In older adults with hypertension, hip fractures accompanied by preoperative acute heartfailure significantly elevate surgical risks and adverse outcomes, necess itating timely identification andmanagement to improve patient outcomes. This s tudy aims to enhance the early recognition of acuteheart failure in older hyper tensive adults prior to hip fracture surgery by developing a predictive modelus ing logistic regression (LR) and machine learning methods, optimizing preoperati ve assessment andmanagement.”

Key words

Hebei/People’s Republic of China/Asia/Cardiology/Cardiovascular Diseases and Conditions/Cyborgs/Emerging Technolog ies/Health and Medicine/Heart Disease/Heart Disorders and Diseases/Heart Fai lure/Hypertension/Machine Learning/Risk and Prevention

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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