Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Quintin P Solano

Biographic Data

ID9599649
NAMEQuintin P Solano
GIVEN NAMESQuintin P
FAMILY NAMESolano
SIGNATURESOLANO Q P
AFFILIATIONSUniversity of Michigan Ann Arbor Michigan USA
ORCID0000-0002-5195-8601
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2024
H-INDEX0
  • The Inequitable Experiences of Left-Handed Medical Students in Surgical Education

    Open Access•Timothy J Gilbert, Maia S Anderson et al.•ARTICLE•Academic Medicine•2024

  • Medical students' perception of their ‘distance travelled’ in medical school applications

    Open Access•Brandon L Ellsworth, Quintin P Solano et al.•ARTICLE•Medical Education•2024

  • Medical Students’ Perception of Their “Distance Traveled” and Its Role in Medical School Applications

    Brandon L Ellsworth, Quintin P Solano et al.•ARTICLE•Academic Medicine•2022

    Purpose: The holistic review of applicants conducted by medical schools includes an assessment of their distance traveled (e.g., hardships overcome) to get to this point on their educational journey. 1 What medical students consider to be distance traveled and how they think it should be included has not been explored. This qualitative study seeks to address this gap in knowledge and centers the voices of medical students by attending to how they…

  • Using Natural Language Processing to Automatically Assess Feedback Quality

    Erkin Ötleş, Daniel E Kendrick et al.•ARTICLE•Academic Medicine•2021

    PURPOSE: Learning is markedly improved with high-quality feedback, yet assuring the quality of feedback is difficult to achieve at scale. Natural language processing (NLP) algorithms may be useful in this context as they can automatically classify large volumes of narrative data. However, it is unknown if NLP models can accurately evaluate surgical trainee feedback. This study evaluated which NLP techniques best classify the quality of surgical t…

No prominent works on this page.

  • Using Natural Language Processing to Automatically Assess Feedback Quality

    Erkin Ötleş, Daniel E Kendrick et al.•ARTICLE•Academic Medicine•2021

    PURPOSE: Learning is markedly improved with high-quality feedback, yet assuring the quality of feedback is difficult to achieve at scale. Natural language processing (NLP) algorithms may be useful in this context as they can automatically classify large volumes of narrative data. However, it is unknown if NLP models can accurately evaluate surgical trainee feedback. This study evaluated which NLP techniques best classify the quality of surgical t…

  • Medical Students’ Perception of Their “Distance Traveled” and Its Role in Medical School Applications

    Brandon L Ellsworth, Quintin P Solano et al.•ARTICLE•Academic Medicine•2022

    Purpose: The holistic review of applicants conducted by medical schools includes an assessment of their distance traveled (e.g., hardships overcome) to get to this point on their educational journey. 1 What medical students consider to be distance traveled and how they think it should be included has not been explored. This qualitative study seeks to address this gap in knowledge and centers the voices of medical students by attending to how they…

  • The Inequitable Experiences of Left-Handed Medical Students in Surgical Education

    Open Access•Timothy J Gilbert, Maia S Anderson et al.•ARTICLE•Academic Medicine•2024

  • Medical students' perception of their ‘distance travelled’ in medical school applications

    Open Access•Brandon L Ellsworth, Quintin P Solano et al.•ARTICLE•Medical Education•2024

Diversity and Career in Medicine (3 works) · Innovations in Medical Education (3 works) · Medical education (3 works) · Medicine (3 works) · Psychology (3 works) · Medical Education and Admissions (2 works) · Medical school (2 works) · Perception (2 works) · Artificial Intelligence (1 works) · Computer Science (1 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae