PREDICTING PROXIMAL FEMORAL REMODELING AFTER SHORT-STEM HIP ARTHROPLASTY: MACHINE LEARNING–AUGMENTED BIOMECHANICAL MODEL
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F25%3A00384906" target="_blank" >RIV/68407700:21220/25:00384906 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
PREDICTING PROXIMAL FEMORAL REMODELING AFTER SHORT-STEM HIP ARTHROPLASTY: MACHINE LEARNING–AUGMENTED BIOMECHANICAL MODEL
Original language description
This study presents a novel hybrid approach that integrates biomechanical modeling with machine learning to evaluate the remodelling of three types of short femoral stems used in THA. The core of the biomechanical analysis was based on the finite element method, which was employed to simulate physiological loading conditions and extract mechanical stimuli. These biomechanical output served as the primary input feature for a machine learning model. The proposed framework enables more efficient optimization of implant designs.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
36th WORKSHOP OF APPLIED MECHANICS BOOK OF PAPERS
ISBN
978-80-01-07452-7
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
9-12
Publisher name
ústav mechaniky, biomechaniky a mechatroniky
Place of publication
Praha
Event location
Praha
Event date
Jun 6, 2025
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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