人工智能 (AI) 的路线图:设计和构建AI准备数据的方法,以促进公平
Farah Kidwai-Khan1, Rixin Wang1, Melissa Skanderson2
1Yale School of Medicine, New Haven, CT, USA; VA Connecticut Healthcare System, West Haven, CT, USA.
Journal of biomedical informatics
|May 13, 2024
概括
本研究介绍了准备电子健康记录数据的方法,以减少人工智能 (AI) 模型中的偏差. 这些可重现的技术提高了数据的表示性和准确性,用于预测患者的跌倒和骨折.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 数据科学数据科学数据科学
背景情况:
- 电子健康记录 (EHR) 数据往往含有偏见,可能会对人工智能 (AI) 模型性能产生负面影响.
- 准备EHR数据对于在医疗保健中开发可靠的AI工具至关重要.
研究的目的:
- 在应用AI之前评估和创建准备EHR数据的方法,以最大限度地减少偏见.
- 开发用于机器学习和自然语言处理的数据框架,用于预测跌倒和骨折.
主要方法:
- 纳入了多种族数据纳入策略,混合数据源 (门诊,住院,结构化,非结构化),并解决了缺少的数据.
- 精选的原始数据使用验证的定义变量,如年龄,种族,性别和医疗保健利用,涉及临床,统计和数据专业知识.
- 利用机器学习来从放射学报告中预测落,以及从DXA扫描报告中进行骨折风险评估的自然语言处理.
主要成果:
- 机器学习处理了超过530万份用于降落预测的报告,从而改善了数据表示和减少了缺失.
- 自然语言处理算法在识别DXA报告中的骨折风险指标时达到98%的准确性.
- 开发的数据准备方法是可重复的,适用于其他AI研究.
结论:
- 输入数据的最佳准备对于减少算法偏差和防止有害的AI输出至关重要.
- 构建AI准备的数据框架可以提高AI应用程序的效率,透明度和可重复性.
- 本研究强调了人工智能实施的关键数据策划方面,以减轻偏见.
相关概念视频
Bias
4.2K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
4.2K
Non-equilibrium in the Cell
4.4K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.4K
Ethics in Research
23.0K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
23.0K
Decision Making
107
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
107
Data Reporting and Recording
4.7K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
4.7K
Ethical Issues
922
Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
Ethical Concerns in Healthcare:
Ethical Concerns in Healthcare:
922


