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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
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Ethical dilemmas in nursing are of utmost importance, as they often arise from the tension between adhering to core ethical principles and the practical realities of healthcare delivery. These dilemmas require nurses to navigate complex situations where competing ethical considerations pull them in different directions.
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儿科人工智能:当前事件和挑战

Brais Galdo1, Carla Pazos2, Jerónimo Pardo3

  • 1Universidad de A Coruña, A Coruña, Spain; INIBIC, A Coruña, Spain; RNASA-IMEDIR, A Coruña, Spain; Complexo Hospitalario Universitario de A Coruña, A Coruña, Spain; Avances en Telemedicina e Informática Sanitaria, A Coruña, Spain.

Anales de pediatria
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概括
此摘要是机器生成的。

人工智能 (AI) 通过改进诊断,治疗和预防来增强儿科护理,与7P医学模型保持一致. 这项技术为彻底改变儿童医疗保健和公共卫生可持续性提供了巨大的潜力.

关键词:
7P 药物是药物中的一种.学习机器学习人工智能的人工智能是人工智能.人工智能的人工智能机器学习是机器学习.这是7P的医药.个性化的医药 (Medicina personalizada) 是一种个性化的药物.儿科 儿科 儿科儿科医院 (Pediatria) 是一个儿童医院.个性化医疗是个性化的医疗.

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科学领域:

  • 儿科医学 儿科医学
  • 人工智能的人工智能
  • 医疗信息学 医疗信息学

背景情况:

  • 人工智能 (AI) 越来越多地融入医疗保健.
  • 7P医学模型 (预测,预防,个性化,精确,参与,外围,多专业) 为现代医疗保健提供了一个框架.
  • 儿科护理在诊断,治疗和资源管理方面面临着独特的挑战.

研究的目的:

  • 检查人工智能在儿科护理中的应用.
  • 评估AI在7P医学模型中的作用.
  • 突出人工智能对儿童疾病管理和公共卫生可持续性的影响.

主要方法:

  • 在儿科环境中审查当前的AI应用.
  • 对人工智能对儿童诊断,治疗和预防的贡献进行分析.
  • 在儿科护理中成功实施AI的案例研究介绍.

主要成果:

  • 人工智能在儿科诊断,治疗和疾病管理中展示了多种应用.
  • 人工智能有助于预防策略和高效的医疗资源管理.
  • 成功案例说明了人工智能对儿科护理的积极影响.

结论:

  • 人工智能有很大的潜力改善儿科护理.
  • 采用人工智能支持向儿科7P医疗模式的过渡.
  • 人工智能集成可以通过改善儿童医疗保健来提高公共卫生系统的可持续性.