Evidence map›Paper›PMID 38137392›Full record

ArticleBiomedicines2023

Deep Learning-Based Knee MRI Classification for Common Peroneal Nerve Palsy with Foot Drop.

Kyung Min Chung, Hyunjae Yu, Jong-Ho Kim, Jae Jun Lee, Jong-Hee Sohn, Sang-Hwa Lee, Joo Hye Sung, Sang-Won Han, Jin Seo Yang, Chulho Kim

Abstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Kyung Min ChungDepartment of Neurosurgery, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.
Hyunjae YuDivision of Big Data and Artificial Intelligence, Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0002-3213-2353
Jong-Ho KimDepartment of Anesthesiology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0002-3818-2239
Jae Jun LeeDepartment of Anesthesiology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.
Jong-Hee SohnDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0003-2656-9222
Sang-Hwa LeeDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0002-0609-1551
Joo Hye SungDepartment of Neurology, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0003-2577-6350
Sang-Won HanDivision of Big Data and Artificial Intelligence, Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.
Jin Seo YangDepartment of Neurosurgery, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0003-4883-7224
Chulho KimDivision of Big Data and Artificial Intelligence, Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24252, Republic of Korea.ORCID 0000-0001-8762-8340

Funding

Hallym University Research Fund (HURF)Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea HI22C1498National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) 2022R1A5A8019303Regional Innovation Strategy (RIS)" through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) 2022RIS-005
6 · The paper itself

Abstract

Foot drop can have a variety of causes, including the common peroneal nerve (CPN) injuries, and is often difficult to diagnose. We aimed to develop a deep learning-based algorithm that can classify foot drop with CPN injury in patients with knee MRI axial images only. In this retrospective study, we included 945 MR image data from foot drop patients confirmed with CPN injury in electrophysiologic tests (

Indexed as

common peroneal nerve palsyconvolutional neural networkdeep learningfoot dropmagnetic resonance image

Identifiers

PMID38137392
PMCPMC10741167

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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.