A Visual Guide to Foregut anatomy: Using Digital Multimedia to Enhance the Learning of Human Gross Anatomy
Bibliographic record
Abstract
Introduction Knowledge of the human gross anatomy is an essential part of a medical student's education, and is equally fundamental for the practicing clinician. Traditionally, medical schools have focused solely on hands‐on cadaver dissections to teach anatomical sciences. However, with the advancements of digital multimedia, it is about time students have other resources at their disposal to enhance their learning of human anatomy. This is particularly important as students rarely have access to the cadavers outside their designated lab times and with the addition of such resources, they will always have the flexibility to strengthen their gross anatomy knowledge, at any time, in any environment. Objectives With the goal of improving students' gross anatomy learning experience, we created a visual, interactive presentation of gross anatomy of the foregut region. The aim was to give the students some background knowledge prior to attending the lab, as well as allowing them to use labeled screenshots from the videos during the lab, and as a study resource after the labs to enhance their learning. Methods The video takes the learners through all the key anatomical structures of the foregut as identified in the first year medical undergraduate curriculum, and uses simple commentary, interactive labeling, and quiz questions to optimize the student learning experience. Results Surveys were distributed amongst 290 medical students before and after they completed the lab to determine whether the videos were helpful. Over 95% of the students felt that the videos made them more prepared for the labs and also, enhanced their learning in the lab. In addition, they reported that they would like to see similar videos for future labs. Conclusion Given the positive feedback, we conclude that this visual guide served to enhance the students' gross anatomy experience, and implementing more of such resources would help with their learning and understanding of the material. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".