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Record W4400253059 · doi:10.4274/dir.2024.242828

Multidisciplinary approach to diagnostic radiology education: a novel educational intervention for Turkish medical students

2024· article· en· W4400253059 on OpenAlex
Parth Patel, Emre Altınmakas, Görkem Ayas, Rachel Stanietzky, Madeline L. Stewart, Abdelrahman Elshikh, Disha Ram, Hrishika Bhosale, Mohamed Eltaher, Serageldin Kamel, Munevver Duran, Umut Yücel, Mohamed Badawy, Scott Rohren, Khaled M. Elsayes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDiagnostic and Interventional Radiology · 2024
Typearticle
Languageen
FieldMedicine
TopicRadiology practices and education
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTurkishLikert scaleMedical educationMultidisciplinary approachSession (web analytics)Medical diagnosisIntervention (counseling)Family medicineRadiologyNursingPsychology

Abstract

fetched live from OpenAlex

Teleconferencing can facilitate a multidisciplinary approach to teaching radiology to medical students.This study aimed to determine whether an online learning approach enables students to appreciate the interrelated roles of radiology and other specialties during the management of different medical cases.Turkish medical students attended five 60-90-minute online lectures delivered by radiologists and other specialists from the United States and Canada through Zoom meetings between November 2020 and January 2021.Student ambassadors from their respective Turkish medical schools recruited their classmates with guidance from the course director.Students took a pretest and posttest to assess the knowledge imparted from each session and a final course survey to assess their confidence in radiology and the value of the course.A paired t-test was used to assess pretest and posttest score differences.A 4-point Likert-type scale was used to assess confidence rating differences before and after attending the course sessions.A total of 1,458 Turkish medical students registered for the course.An average of 437 completed both pre-and posttests when accounting for all five sessions.Posttest scores were significantly higher than pretest scores for each session (P < 0.001).A total of 546 medical students completed the final course survey evaluation.Students' rating of their confidence in their radiology knowledge increased after taking the course (P < 0.001).Students who took our course gained an appreciation for the interrelated roles of different specialties in approaching medical diagnoses and interpreting radiological findings.These students also reported an increased confidence in radiology topics and rated the course highly relevant and insightful.Overall, our findings indicated that multidisciplinary online education can be feasibly implemented for medical students by video teleconferencing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.395
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it