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Record W7036008476

Assessment of hip fracture risk using cross-section strain energy determined from QCT-based finite element model

2015· dissertation· en· W7036008476 on OpenAlexfundno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaManitoba Health Research Council
KeywordsHip fractureFracture (geology)Finite element methodCancellous boneFemurFemoral neckRisk assessmentStrain (injury)
DOInot available

Abstract

fetched live from OpenAlex

Accurate assessment of hip fracture risk is very important to prevent hip fracture and to monitor the effect of a treatment. A subject-specific QCT-based finite element model was constructed to assess hip fracture risk at the critical locations of femur during the single-leg stance and the sideways fall. The aim of this study was to improve the prediction of hip fracture risk by introducing a more proper failure criterion to more accurately describe bone failure mechanism. Hip fracture risk index was defined using the strain energy criterion, which is able to integrally consider information such as stresses, strains and material properties in bone failure. It was found that the femoral neck and the intertrochanteric region have higher fracture risk than other part of the femur, probably owing to the larger content of cancellous bone in these regions. The study results also suggested that women are more prone to hip fracture than men. The effects of different parameters such as age, body height, weight, and BMI on hip fracture risk were also investigated in this study. The findings in this study have a good agreement with those clinical observations reported in the literature. The main contributions from this study include: (1) introducing an algorithm for hip fracture risk assessment at the critical locations of femur using the strain energy criterion and QCT-based finite element modeling, (2) theoretically more reasonable definition of hip fracture risk index based on the strain energy criterion, and (3) a semi-automatic finite element analysis and automatic calculation of hip fracture risk index at the critical locations of femur using in-house developed computer codes. The proposed hip fracture risk index based on the strain energy criterion will be a promising tool for more accurate assessment of hip fracture risk. However, experimental validation should be conducted before its clinical applications.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations0
Published2015
Admission routes1
Has abstractyes

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