Evidence map›Paper›PMID 34539089›Full record

ArticleNeural computing & applications2022

Adaptive kernel selection network with attention constraint for surgical instrument classification.

Yaqing Hou, Wenkai Zhang, Qian Liu, Hongwei Ge, Jun Meng, Qiang Zhang, Xiaopeng Wei

Abstract read
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In one paragraph

Article in Neural computing & applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yaqing HouSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.ORCID 0000-0002-9929-2650
Wenkai ZhangSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Qian LiuSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Hongwei GeSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Jun MengSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Qiang ZhangSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.
Xiaopeng WeiSchool of Computer Science and Technology, Dalian University of Technology, Dalian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computer vision (CV) technologies are assisting the health care industry in many respects, i.e., disease diagnosis. However, as a pivotal procedure before and after surgery, the inventory work of surgical instruments has not been researched with the CV-powered technologies. To reduce the risk and hazard of surgical tools' loss, we propose a study of systematic surgical instrument classification and introduce a novel attention-based deep neural network called SKA-ResNet which is mainly composed of: (

Indexed as

Attention mechanismDeep learningFine-grained classificationHealth care

Identifiers

PMID34539089
PMCPMC8435567

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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.