Bibliographic record
Abstract
El médico clínicamente competente es un profesional que se destaca por la eficiencia y eficacia de su razonamiento clínico (RC). Diversos estudios han demostrado que el RC del experto se logra cuando los conocimientos pertinentes se organizan en redes cognitivas que son utilizadas para hacer diagnósticos y decidir conductas de manera no analítica y luego pueden ser corroborados mediante el método hipotético-deductivo (analítico e iterativo). En cambio el novato, aunque posea los conocimientos necesarios, no ha desarrollado aún las redes cognitivas que facilitan el acceso a estos conocimientos en forma rápida, eficaz y precisa. Por lo tanto, el proceso de diagnóstico de un novato se realiza principalmente a través de un razonamiento clínico de tipo analítico solamente. Este tipo de RC se basa en un procesamiento de la información más lento - de tipo hipotético-deductivo - que apela tanto a los conocimientos biomédicos como clínicos, con predominio de los primeros.Dada la trascendencia del RC en la práctica médica, es importante tener la posibilidad de medir esta capacidad durante el desarrollo profesional. El objetivo de esta revisión es analizar el estado del arte sobre el tema de razonamiento clínico y su evaluación en la Carrera de Medicina. ABSTRACTClinical Reasoning Development in Medicine. The competent clinician excels in efficient and effective clinical reasoning (CR). Modern cognitive theories propose that the expert’s CR is achieved by the organization of pertinent knowledge into adequate cognitive networks that allow the selection of diagnostic hypothesis and appropriate decision-making in a non-analytical manner. Afterwards, hypothetic-deductive reasoning is used to corroborate or reject the considered hypothesis.However, the novice one, who may have the adequate and necessary knowledge, has not yet developed the appropriate cognitive networks that facilitate a fast and efficient access to knowledge. Thus, the novices come to diagnoses by using analytical reasoning (hypothetic-deductive and iterative reasoning), which is a slower way to come to diagnosis. Novice CR involves biomedical and clinical knowledge with predominance of the former.Efficient CR constitutes a crucial characteristic for competent clinicians; hence certification of CR is of the utmost importance in Medical Education. Thereby, the development of dependable clinical reasoning (CR) evaluations constitutes an important goal. This review focuses on the state of the art in clinical reasoning and its evaluation alternatives in Medicine.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".