Evidence map›Paper›PMID 41201165›Full record

ArticleInternational journal for numerical methods in biomedical engineering2025

Multi-Objective Optimization of Dental Implant Designs With Multi-Recessed Holes: Insights From Static and Dynamic Finite Element Analysis.

I-Chiang Chou, Shih-Hao Huang, Cheng-Kang Lee, Mayur Jiyalal Prajapati, Jian-Cheng Huang, Yung-Chang Cheng, Cho-Pei Jiang

Abstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Development of Design-Phase Digital Twin for Structural Optimization of a Biomedical Device.International journal for numerical methods in biomedical engineering · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

I-Chiang ChouDepartment of Stomatology, Yangming Branch, Taipei City Hospital, Taipei, Taiwan.
Shih-Hao HuangGraduate Institute of Manufacturing Technology, National Taipei University of Technology, Taipei, Taiwan.
Cheng-Kang LeeDepartment of Industrial Engineering and Management, Cheng Shiu University, Kaohsiung, Taiwan.
Mayur Jiyalal PrajapatiHigh-Value Biomaterial Research and Commercialization Center, National Taipei University of Technology, Taipei, Taiwan.
Jian-Cheng HuangDepartment of Mechatronics Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Yung-Chang ChengDepartment of Mechatronics Engineering, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan.
Cho-Pei JiangDepartment of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan.ORCID https://orcid.org/0000-0002-7933-7356

Funding

National Science and Technology Council, Taiwan 113-2622-E-027-023National Science and Technology Council, Taiwan 114-2923-E-027-004-MY3
6 · The paper itself

Abstract

This study presents a novel dental implant design featuring multi-recessed holes, developed through an integrated multi-objective optimization framework. The impact of the implant geometry on longevity, strength, and success rate is explored under both static and dynamic loading conditions. The novel design features multi-recessed holes, and five key implant parameters are selected as control factors for optimization. Experimental simulations are conducted using the uniform design (UD) method. Finite element analysis (FEA) is used to simulate the implant system to evaluate the fatigue safety factor and equivalent stress at the primary, middle, and final stages of osseointegration. Additionally, the dynamic FEA is employed to calculate the maximum micromotion under dynamic chewing loads. To maximize the fatigue safety factor and minimize equivalent stress and micromotion, a multi-objective optimization approach is applied, integrating Kriging interpolation (KGI), entropy weighting analysis (EWA), the technique for order preference by similarity to ideal solution (TOPSIS), and genetic algorithms (GA). The optimal design achieves a fatigue safety factor of 3.022 and an equivalent stress of 459.49 MPa, with improvements of 28.1% and 3.2%, respectively, compared to the original design. Furthermore, the optimized design results in a micromotion of 32.96 μm, reflecting a 37.1% improvement. Overall, the multi-objective optimization process enhances the implant's safety factor and strength under various loading conditions.

Indexed as

Dental ImplantsDental Prosthesis DesignFinite Element AnalysisAlgorithmsComputer SimulationHumansStress, MechanicalDental Implantsfatigue safety factorgenetic algorithmKriging interpolationmicromotionmulti‐recessed holes implant systemTOPSISuniform design

Identifiers

PMID41201165
PMCPMC12593267

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.