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Factors Affecting the Risk of Infection01:26

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The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
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Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
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Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
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The International System of Units or SI system, by international agreement, has fixed measurement units for seven fundamental properties: length, mass, time, temperature, electric current, amount of substance, and luminosity. These are called the SI base units.
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Updated: Feb 3, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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在非重症监护病房患者中出现术后妄想的危险因素:机器学习方法.

Hyungbok Lee1, Taesa Ahn, Sohyeon Park

  • 1Nursing Department, Seoul National University Hospital, Seoul, Republic of Korea.

Computers, informatics, nursing : CIN
|February 2, 2026
PubMed
概括

研究人员确定了一般医院患者中术后妄想的主要危险因素. 机器学习模型可以使用电子健康记录来预测这种并发症,从而改善患者的护理.

关键词:
可解释的人工智能机器学习 机器学习手术后妄症 术后妄症预测模型的预测模型.

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科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能在医学中的应用
  • 老年医学 老年医学

背景情况:

  • 手术后痴呆症是手术患者常见和严重的并发症.
  • 目前用于一般病房患者的预测工具是不够的.
  • 早期识别风险患者对于及时干预至关重要.

研究的目的:

  • 在非重症监护病房 (非ICU) 患者中确定术后妄想的重大风险因素.
  • 开发和评估用于预测术后妄想的机器学习模型.
  • 利用电子健康记录 (EHR) 数据改善临床决策.

主要方法:

  • 从2017年到2022年,对85,884名手术患者进行了回顾性分析.
  • 从EHR数据中利用了53个潜在的预测变量.
  • 采用机器学习算法,LightGBM表现出最佳性能.

主要成果:

  • 较高的并发症数量,晚年,增加的排水数量,升高的和降低的白蛋白水平被确定为关键风险因素.
  • 在大多数外科专业中,年龄是最重要的预测因素.
  • 重症监护室 (ICU) 的转移成为神经外科手术中的一个关键因素.

结论:

  • 使用EHR数据的基于AI的预测模型可以有效地识别患有术后妄想风险的患者.
  • 这些发现为制定有针对性的干预措施以减轻妄想风险提供了基础.
  • 这种方法有可能提高一般外科病房的患者护理和结果.