Marianne M Green
Biographic Data
| ID | 8306299 |
|---|---|
| NAME | Marianne M Green |
| GIVEN NAMES | Marianne M |
| FAMILY NAME | Green |
| SIGNATURE | GREEN M M |
| AFFILIATIONS | Twitter (United States) |
| ORCID | 0000-0002-0721-2095 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Using Natural Language Processing to Visualize Narrative Feedback in a Medical Student Performance Dashboard
Employing Natural Language Processing to Evaluate the Impact of an Intervention to Reduce Narrative Bias Within Medical Student Clerkship Assessments
Purpose: Studies have demonstrated the deleterious impact of bias within clinical assessments, especially for students from minoritized groups.1–3 Growing evidence demonstrates that words in narrative assessments differ based on race and gender in both clinical performance assessments2 (CPAs) and within Medical Student Performance Evaluations3 (MSPEs). We developed and implemented a brief intervention to promote best practices and reduce bias in …
Automated Assessment of Medical Students’ Competency-Based Performance Using Natural Language Processing (NLP)
Assessment systems in competency-based medical education increasingly rely on narrative feedback to describe learner performance. 1 When collected over time, learner portfolios include hundreds of narrative comments describing behavioral performance such as communication and teamwork that are not evident in categorical ratings or quantitative assessments alone. However, this large volume of data makes summative competency assessment both time and…
We Have No Choice but to Transform
Medical education exists to prepare the physician workforce that our nation needs, but the COVID-19 pandemic threatened to disrupt that mission. Likewise, the national increase in awareness of social justice gaps in our country pointed out significant gaps in health care, medicine, and our medical education ecosystem. Crises in all industries often present leaders with no choice but to transform—or to fail. In this perspective, the authors sugges…
Northwestern University Feinberg School of Medicine
Medical Education Program Highlights Northwestern University Feinberg School of Medicine (Feinberg) is a large urban medical school with 634 students based in Chicago, Illinois. The curriculum has 3 phases. Phase 1 consists of foundational material and 14 organ-based modules. Phase 2 consists of 6 core clerkships, and Phase 3 is composed of advanced clinical clerkships. Feinberg’s curriculum is organized around 8 competencies: patient-centered me…
Standardizing and Improving the Content of the Dean's Letter
The medical student performance evaluation, known as the MSPE or dean's letter, summarizes a medical student's performance at the time of application for postgraduate training. In each medical school, considerable effort is exerted to produce this longitudinal account of performance. For the MSPE to be valuable it should serve as an objective and unabridged summary of the student's performance without obscuring or eliminating the very information…
No prominent works on this page.
Standardizing and Improving the Content of the Dean's Letter
The medical student performance evaluation, known as the MSPE or dean's letter, summarizes a medical student's performance at the time of application for postgraduate training. In each medical school, considerable effort is exerted to produce this longitudinal account of performance. For the MSPE to be valuable it should serve as an objective and unabridged summary of the student's performance without obscuring or eliminating the very information…
Northwestern University Feinberg School of Medicine
Medical Education Program Highlights Northwestern University Feinberg School of Medicine (Feinberg) is a large urban medical school with 634 students based in Chicago, Illinois. The curriculum has 3 phases. Phase 1 consists of foundational material and 14 organ-based modules. Phase 2 consists of 6 core clerkships, and Phase 3 is composed of advanced clinical clerkships. Feinberg’s curriculum is organized around 8 competencies: patient-centered me…
Automated Assessment of Medical Students’ Competency-Based Performance Using Natural Language Processing (NLP)
Assessment systems in competency-based medical education increasingly rely on narrative feedback to describe learner performance. 1 When collected over time, learner portfolios include hundreds of narrative comments describing behavioral performance such as communication and teamwork that are not evident in categorical ratings or quantitative assessments alone. However, this large volume of data makes summative competency assessment both time and…
We Have No Choice but to Transform
Medical education exists to prepare the physician workforce that our nation needs, but the COVID-19 pandemic threatened to disrupt that mission. Likewise, the national increase in awareness of social justice gaps in our country pointed out significant gaps in health care, medicine, and our medical education ecosystem. Crises in all industries often present leaders with no choice but to transform—or to fail. In this perspective, the authors sugges…
Employing Natural Language Processing to Evaluate the Impact of an Intervention to Reduce Narrative Bias Within Medical Student Clerkship Assessments
Purpose: Studies have demonstrated the deleterious impact of bias within clinical assessments, especially for students from minoritized groups.1–3 Growing evidence demonstrates that words in narrative assessments differ based on race and gender in both clinical performance assessments2 (CPAs) and within Medical Student Performance Evaluations3 (MSPEs). We developed and implemented a brief intervention to promote best practices and reduce bias in …
Using Natural Language Processing to Visualize Narrative Feedback in a Medical Student Performance Dashboard
Innovations in Medical Education (6 works) · Clinical Reasoning and Diagnostic Skills (4 works) · Medical education (4 works) · Medicine (4 works) · Psychology (4 works) · Curriculum (3 works) · Narrative (3 works) · Computer Science (2 works) · Empathy and Medical Education (2 works) · Linguistics (2 works)