Evidence map›Paper›PMID 37627837›Full record

ArticleBioengineering (Basel, Switzerland)2023

Preoperative Planning Framework for Robot-Assisted Dental Implant Surgery: Finite-Parameter Surrogate Model and Optimization of Instrument Placement.

Yan Wang, Wei Wang, Yueri Cai, Qiming Zhao, Yuyang Wang

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Yan WangSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.ORCID 0000-0003-1374-8168
Wei WangSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Yueri CaiSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Qiming ZhaoSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Yuyang WangSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
Beihang University · CN

Funding

National Key Research and Development Program of China 2020YFB1312800
6 · The paper itself

Abstract

For robot-assisted dental implant surgery, it is necessary to feed the instrument into a specified position to perform surgery. To improve safety and efficiency, a preoperative planning framework, including a finite-parameter surrogate model (FPSM) and an automatic instrument-placement method, is proposed in this paper. This framework is implemented via two-stage optimization. In the first stage, a group of closed curves in polar coordinates is used to represent the oral cavity. By optimizing a finite number of parameters for these curves, the oral structure is simplified to form the FPSM. In the second stage, the FPSM serves as a fast safety estimator with which the target position/orientation of the instrument for the feeding motion is automatically determined through particle swarm optimization (PSO). The optimized feeding target can be used to generate a virtual fixture (VF) to avoid undesired operations and to lower the risk of collision. This proposed framework has the advantages of being safe, fast, and accurate, overcoming the computational burden and insufficient real-time performance of complex 3D models. The framework has been developed and tested, preliminarily verifying its feasibility, efficiency, and effectiveness.

Indexed as

dental implant surgeryparticle swarm optimizationsurrogate modelvirtual fixture

Identifiers

PMID37627837
PMCPMC10451750
OpenAlexW4385762623

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.