机器学习程序用于泌尿外科医生奖学金申请人审查的使用
Nicole J Wood1, Leslie Rickey2, Christine Vaccaro3
1Department of Urogynecology, Hartford Hospital, Hartford.
Urogynecology (Philadelphia, Pa.)
|February 2, 2026
概括
一个新的机器学习程序,Halsted,显示了一个强大的正相关性与节目主任评价选择奖学金申请人. 这种人工智能工具有可能减少医疗培训应用中的偏见和行政负担.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 手术培训申请审查 应用程序审查
背景情况:
- 缺乏审查高级医学培训申请的客观方法.
- 程序主管 (PD) 审查是标准的,但可以是主观的和耗时的.
研究的目的:
- 评估Halsted机器学习程序在泌尿后科学术奖学金申请人选择中的准确性.
- 为了比较Halsted的申请人评估与传统的项目总监评价.
主要方法:
- 在3个泌尿和妇科学术奖学金计划中进行了比较研究.
- 项目主管 (PD) 在100分尺度上对126个奖学金申请进行了评分.
- 哈尔斯特德计划的分数与PD分配的分数进行了比较.
主要成果:
- 在三个项目中的两个项目中,在Halsted和PD分数之间发现了强烈的正相关性 (r=0.60,P=0.0019;r=0.58,P<0.001).
- 在第三个程序中观察到微弱的正相关性 (r=0.33,P=0.0225).
- 在PD和Halsted评估中,在申请人得分方面发现了显著的项目间差异.
结论:
- 哈尔斯特计划与PD排名有显著的正相关性,表明其作为客观审查工具的潜力.
- 排名的项目间变化凸显了奖学金选择的个性化性质.
- 机器学习为减轻偏见和减少医学培训应用程序审查中的行政工作量提供了一个有希望的途径.
相关概念视频
Review and Preview
8.4K
In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
Percentiles are a type of fractile that partition data into...
8.4K
Review and Preview
11.3K
Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
11.3K
Machines
579
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.
A free-body diagram of the...
A free-body diagram of the...
579
Machines: Problem Solving II
668
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
668
Machines: Problem Solving I
714
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
714
Avoidance Learning and Learned Helplessness
2.6K
Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
2.6K


