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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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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.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

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Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
798
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

485
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
485
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

294
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
294
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

43
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
43
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
56

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相关实验视频

Updated: May 31, 2025

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

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通过区域计算优化医疗保健大数据性能.

Tariq Alsahfi1, Afzal Badshah2, Omar Ibrahim Aboulola3

  • 1Department of Information Systems and Technology, University of Jeddah, Jeddah, Saudi Arabia. tmalsahfi@uj.edu.sa.

Scientific reports
|January 24, 2025
PubMed
概括
此摘要是机器生成的。

区域计算 (RC) 解决了医疗保健大数据 (HBD) 的挑战. 这种方法在区域范围内处理医疗数据,减少云延迟,实现实时分析和改善患者护理.

关键词:
医疗保健 医疗保健 医疗保健 医疗保健医疗保健大数据 医疗保健大数据医疗事物的互联网 (IoMT)区域计算 区域计算

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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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相关实验视频

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Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

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科学领域:

  • 数字健康数字健康
  • 医疗信息学 医疗信息学
  • 数据科学数据科学数据科学

背景情况:

  • 医疗保健行业正在经历数字化转型,包括医疗物联网 (IOMT),电子健康记录 (EHR) 和可穿戴设备等技术.
  • 这种数字化转变产生了大量的医疗保健大数据 (HBD),需要高效的分析来改善患者的治疗结果和护理.
  • 传统的基于云计算的处理面临延迟和网络拥堵问题,大型的,时间敏感的HBD,阻碍实时应用程序.

研究的目的:

  • 提出一个区域计算 (RC) 范式来管理医疗保健大数据 (HBD).
  • 为了减轻与HBD集中的云处理相关的延迟和网络拥堵挑战.
  • 实现及时,实时的数据分析,以加强医疗保健决策.

主要方法:

  • 该研究提出了一个区域计算 (RC) 框架.
  • 该框架利用战略位置的区域服务器进行本地化数据收集,处理和存储.
  • 该RC方法旨在减少对集中式云基础设施的依赖,特别是在高峰负载期间.

主要成果:

  • 该RC范式有效地减少了医疗保健大数据 (HBD) 处理的延迟.
  • 区域化数据管理促进了地方一级的实时分析.
  • 该框架减轻了传统云计算对时间敏感的医疗数据所施加的限制.

结论:

  • 区域计算 (RC) 为管理医疗保健大数据 (HBD) 挑战提供了可行的解决方案.
  • 这种方法提高了医疗保健提供者利用实时数据进行个性化和优化患者护理的能力.
  • RC赋予了数据驱动的决策能力,从而改善了诊断,监测和外科干预.