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Record W1491226180 · doi:10.25011/cim.v30i4.2798

38. Max Brodel (1870-1941): His artistic influence on surgical learning at John Hopkins Medical School

2007· article· en· W1491226180 on OpenAlexvenueno aff
P. Pace-Asciak, Toby Gelfand

Bibliographic record

VenueClinical and investigative medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsGermanGraduation (instrument)MedicineMedical schoolMedical educationHistoryEngineering

Abstract

fetched live from OpenAlex

Medical students depend on illustration to learn anatomical facts and details that may be too subtle for the written or spoken word. For surgical disciplines, learners rely on tools such as language, 2-dimensional illustrations, and 3-dimensional models to pass on important concepts. Although a photograph can convey factual information, illustration can highlight and educate the pertinent details for understanding surgical procedures, neurovascular structures, and the pathological disease processes.
 In order to understand the current role of medical illustration in education, one needs to look to the past to see how art has helped solve communication dilemmas when learning medicine. This paper focuses on Max Brodel (1870-1941), a German-trained artist who eventually immigrated to the United States to pursue his career as a medical illustrator. Shortly after his arrival in Baltimore, Brodel made significant contributions to medical illustration in Gynecology at John Hopkins University, and eventually in other fields of medicine such as Urology and Otolaryngology. Brodel is recognized as one of America’s most distinguished medical illustrators for creating innovative artistic techniques and founding the profession of medical illustration. 
 Today, animated computer based art is synergistically used with medical illustration to educate students about anatomy. Some of the changes that have occurred with the advancement of computer technology will be highlighted and compared to a century ago, when illustrations were used for teaching anatomy due to the scarcity of cadavers. 
 Schultheiss D, Udo J. Max Brodel (1870-1941) and Howard A.Kelly (1858-1943) – Urogynecology and the birth of modern medical illustration. European Journal of Obstetrics & gynecology and Reproductive Biology 1999; 86:113-115.
 Crosby C. Max Brodel: the man who put art into medicine. New York: Springer-Verlag, 1991. 
 Papel ID. Max Brodel’s contributions to otolaryngology – Head and Neck surgery. The American Journal of Otology 1986; 7(6):460-469.

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.

How this classification was reachedexpand

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)0.005
metaresearch head score (Gemma)0.070
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.070
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.020
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.375
Teacher spread0.279 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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