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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.
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Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
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Updated: Aug 9, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Using artificial intelligence in medical school admissions screening to decrease inter- and intra-observer

Graham Keir1, Willie Hu2, Christopher G Filippi3

  • 1Department of Radiology, Northwell Health, Manhasset, New York, USA.

JAMIA Open
|February 23, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can standardize medical school admissions, reducing variability. An AI model achieved 88% accuracy, demonstrating feasibility for fair and systematic applicant screening.

Failed At:

2026-06-19T13:40:00.740288+00:00

Keywords:
admissionsartificial intelligencebiasmachine learningmedical education

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