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Le droit de l'imagerie médicale et ses enjeux de santé publique : étude comparative France, Angleterre, Allemagne et Québec

2017· dissertation· W7147497776 on OpenAlexaboutno aff
Nesrine Benyahia

Bibliographic record

Venuenot available
Typedissertation
Language
FieldHealth Professions
TopicQuality and Safety in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsPatient rightsContext (archaeology)Liability

Abstract

fetched live from OpenAlex

L'imagerie médicale est une activité de soins à la croisée de toutes les spécialités médicales. Elle est devenue une activité de soins primordiale au coeur du diagnostic et du traitement de nombreuses pathologies en oncologie, neurologie et cardiologie, par exemple. Son rôle essentiel dans le parcours de soins du patient est le résultat du développement important des technologies, mais également des indications cliniques. L'encadrement de l'imagerie médicale dans le système de santé français reste néanmoins flou et bordé de contraintes juridiques et économiques. Ce flou juridique et économique est un frein à l'accès effectif aux techniques d'imagerie médicale pour les patients à travers notamment un contrôle exacerbé des installations des équipements et une tarification des actes désorganisée. Par ailleurs, l'absence d'évaluations médico-économiques retarde l'implémentation des innovations et crée même des risques d'atteinte à la sécurité et à la qualité des examens d'imagerie réalisés.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.359

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.008
Science and technology studies0.0040.002
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.106
GPT teacher head0.484
Teacher spread0.378 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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