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相关概念视频

Quality Assurance01:19

Quality Assurance

3.8K
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
3.8K
Data Validation01:03

Data Validation

7.2K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
7.2K
Reliability and Validity01:29

Reliability and Validity

14.3K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
14.3K
Testing Water Quality01:14

Testing Water Quality

440
When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
440
Nursing Process for Patient and Caregiver Teaching III: Evaluation and Documentation01:20

Nursing Process for Patient and Caregiver Teaching III: Evaluation and Documentation

2.7K
Evaluation of the teaching process enables the nurse to determine if the patient's learning needs were met and if training was effective. If the expected outcomes are not met, the care plan is revised, and additional education or reinforcement is provided. Nurses can ask questions after the session or obtain feedback to assess the patient's understanding of the topic.
Nurses can use several methods to evaluate patient outcomes. For example, oral questions can assess cognitive learning,...
2.7K
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

666
Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
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相关实验视频

Updated: Mar 18, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke
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Computerized Adaptive Testing System of Functional Assessment of Stroke

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人工智能测试,评估,验证和验证可访问性:一个全面的框架.

Gabriella Waters1,2

  • 1Cognitive and Neurodiversity AI Lab, Center for Responsible AI, Virginia State University, Baltimore, VA, United States.

Frontiers in digital health
|March 16, 2026
PubMed
概括
此摘要是机器生成的。

本研究引入了一个AI测试,评估,验证和验证 (TEVV) 框架,以确保人工智能 (AI) 系统可访问. 评估AI的可访问性障碍和偏见可以增强所有用户的包容性.

关键词:
人工智能评估AI评估人工智能评估框架人工智能测试的人工智能测试可访问性 (对于残疾人)人工智能的人工智能是人工智能.

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Methods to Test Visual Attention Online
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Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System
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Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

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相关实验视频

Last Updated: Mar 18, 2026

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Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

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Methods to Test Visual Attention Online
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Methods to Test Visual Attention Online

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科学领域:

  • 计算机科学 计算机科学
  • 人与计算机的交互
  • 人工智能伦理学 人工智能伦理学

背景情况:

  • 人工智能 (AI) 系统越来越多地融入社会.
  • 确保残疾人能够使用人工智能对于公平的技术采用至关重要.

研究的目的:

  • 为人工智能测试,评估,验证和验证 (TEVV) 提供一个全面的框架,特别关注可访问性.
  • 提高人工智能技术对不同用户群体的包容性和有效性.

主要方法:

  • 开发了一个TEVV框架,包括红色团队,模型测试和现场测试.
  • 强调了针对可访问性的可用性测试.
  • 进行了详细的案例研究来验证框架.

主要成果:

  • 使用该框架进行的系统评估确定了人工智能系统中的可访问性障碍和偏见.
  • 该框架展示了AI包容性和对不同用户有效性的改进.
  • 案例研究提供了框架实用性的经验证据.

结论:

  • 专注于可访问性的TEVV框架为开发公平的人工智能提供了一个结构化的方法.
  • 实施这个框架会导致普遍可用的AI系统.
  • 这种方法支持创建有利于社会所有成员的AI.