Deep Learning-Enhanced Hand Grip and Release Test for Degenerative Cervical Myelopathy: Shortening Assessment Duration to 6 Seconds
Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use...
Saved in:
Published in | Neurospine Vol. 21; no. 1; pp. 46 - 56 |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Korea (South)
Korean Spinal Neurosurgery Society
01.03.2024
대한척추신경외과학회 |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test.Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration.Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT.Conclusion: DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance. |
---|---|
AbstractList | Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test.
The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration.
Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT.
DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance. Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test.OBJECTIVEHand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test.The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration.METHODSThe retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration.Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT.RESULTSPatients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT.DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.CONCLUSIONDL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance. Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DLHGRT. Conclusion: DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance. KCI Citation Count: 0 Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test.Methods: The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration.Results: Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT.Conclusion: DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance. |
Author | Wu, Weihao Yu, Zhengran Chen, Chong Liao, Tianying Chang, Yunbing Chen, Junying Ye, Yongyu Yu, Tao Liang, Guoyan |
Author_xml | – sequence: 1 givenname: Yongyu orcidid: 0000-0002-7941-4008 surname: Ye fullname: Ye, Yongyu – sequence: 2 givenname: Yunbing orcidid: 0009-0000-8399-7798 surname: Chang fullname: Chang, Yunbing – sequence: 3 givenname: Weihao orcidid: 0009-0003-5838-633X surname: Wu fullname: Wu, Weihao – sequence: 4 givenname: Tianying orcidid: 0009-0009-5004-4371 surname: Liao fullname: Liao, Tianying – sequence: 5 givenname: Tao orcidid: 0009-0004-9897-3165 surname: Yu fullname: Yu, Tao – sequence: 6 givenname: Chong orcidid: 0000-0003-1824-6116 surname: Chen fullname: Chen, Chong – sequence: 7 givenname: Zhengran orcidid: 0000-0001-6733-6332 surname: Yu fullname: Yu, Zhengran – sequence: 8 givenname: Junying orcidid: 0000-0002-5614-9731 surname: Chen fullname: Chen, Junying – sequence: 9 givenname: Guoyan orcidid: 0000-0003-0072-3156 surname: Liang fullname: Liang, Guoyan |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38569631$$D View this record in MEDLINE/PubMed https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART003067418$$DAccess content in National Research Foundation of Korea (NRF) |
BookMark | eNp1kk1vEzEQhleoiJbSMzfkI0JKu15_rbmgKCltpSCkNpytWe9sYrqxU3sTqWf-OG4SKorEaUb2-z4z9szb4sgHj0XxnpbnlFdcXPh0XjGuWCXPpWSvipNK1HIkhaZHz3nNjouzlFxTcq4EZ4y-KY5ZLaSWjJ4Uv6aIazJDiN75xejSL8FbbMk1-JZcRbcmT8kt9ggJyRzTQLoQyRQX6DHC4LZIJhi3zkJPvj1iH9YwLB8_k7tliAM-Qck4JUxphX4g082TJ3gyBCLJHdrg2_SueN1Bn_DsEE-LH18v55Pr0ez71c1kPBtZrsUw4mWjGtu0XUutVrXS1CrOaKdBtUza_BwFoKmuKDLBJaWgLGhopOiqWnFgp8WnPdfHztxbZwK4XVwEcx_N-HZ-Y2jJac2kyOKbvbgN8NOso1tBfNw5dgchLgzEwdkeDUCGd11d27bjoqpr3amq4lwoCbpUZWZ92bPWm2aFrc0_EaF_AX15490yN7XN3WhdSVFlwscDIYaHTZ6CWblkse_BY9gkw0rGylLnuWbph7-LPVf5M_MsuNgLbAwpReyeJbQ0u8UyPpnDYpm8WNkh_nFYN-zmmLt1_X99vwHwvNGf |
CitedBy_id | crossref_primary_10_1136_bmjno_2024_000913 |
Cites_doi | 10.1007/s00586-022-07349-x 10.21037/atm.2016.08.57 10.1097/brs.0000000000004243 10.1097/brs.0000000000001849 10.1007/s00586-017-4949-2 10.1007/s00586-017-4948-3 10.1302/0301-620x.69b2.3818752 10.1097/01.brs.0000190452.33258.72 10.1302/0301-620x.90b9.20459 10.1155/2018/5138234 10.1093/neuros/nyz499 10.1109/jbhi.2022.3184870 10.1016/j.apmr.2004.01.037 10.1007/s00776-013-0381-6 10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 10.1097/01.bsd.0000203275.97627.9f 10.1177/20552076231179030 10.1177/1073858412467377 10.1097/brs.0000000000003696 10.1016/j.clineuro.2019.105414 |
ContentType | Journal Article |
Copyright | Copyright © 2024 by the Korean Spinal Neurosurgery Society 2024 |
Copyright_xml | – notice: Copyright © 2024 by the Korean Spinal Neurosurgery Society 2024 |
DBID | AAYXX CITATION NPM 7X8 5PM DOA ACYCR |
DOI | 10.14245/ns.2347326.663 |
DatabaseName | CrossRef PubMed MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals Korean Citation Index |
DatabaseTitle | CrossRef PubMed MEDLINE - Academic |
DatabaseTitleList | PubMed MEDLINE - Academic CrossRef |
Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
EISSN | 2586-6591 |
EndPage | 56 |
ExternalDocumentID | oai_kci_go_kr_ARTI_10418365 oai_doaj_org_article_aa4a3ff88cdf452889f72244576a9070 PMC10992652 38569631 10_14245_ns_2347326_663 |
Genre | Journal Article |
GrantInformation_xml | – fundername: Basic and Applied Basic Research Foundation of Guangdong Province grantid: 2023A1515030001 – fundername: Basic and Applied Basic Research Foundation of Guangdong Province grantid: 2020A1515110545 – fundername: e Guangzhou Municipal Science and Technology Project grantid: 2023A04J0500 – fundername: Guangdong Provincial People's Hospital grantid: KY0120220040 – fundername: Basic and Applied Basic Research Foundation of Guangdong Province grantid: 2022A1515111091 – fundername: Basic and Applied Basic Research Foundation of Guangdong Province grantid: 2021A1515012651 – fundername: Basic and Applied Basic Research Foundation of Guangdong Province grantid: 2022A1515012557 |
GroupedDBID | AAYXX ABDBF ADBBV ALMA_UNASSIGNED_HOLDINGS AOIJS BCNDV CITATION GROUPED_DOAJ HYE PGMZT RPM M~E NPM 7X8 5PM ACYCR OK1 |
ID | FETCH-LOGICAL-c495t-40b7bcbdfd1c978791c7431f9a7d36c6317aa91921e354611a7ca9ab65f2874a3 |
IEDL.DBID | DOA |
ISSN | 2586-6583 |
IngestDate | Thu Apr 04 10:27:16 EDT 2024 Wed Aug 27 01:16:08 EDT 2025 Thu Aug 21 18:34:42 EDT 2025 Thu Jul 10 18:39:41 EDT 2025 Thu Jul 10 06:32:19 EDT 2025 Thu Apr 24 23:02:03 EDT 2025 Tue Jul 01 01:58:18 EDT 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Keywords | Deep learning Degenerative cervical myelopathy Diagnostic performance Shortened assessment duration 10-Second grip and release test |
Language | English |
License | This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c495t-40b7bcbdfd1c978791c7431f9a7d36c6317aa91921e354611a7ca9ab65f2874a3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Yongyu Ye and Yunbing Chang contributed equally to this study as co-first authors. https://doi.org/10.14245/ns.2347326.663 |
ORCID | 0000-0003-1824-6116 0009-0004-9897-3165 0000-0002-7941-4008 0009-0003-5838-633X 0009-0009-5004-4371 0000-0003-0072-3156 0000-0002-5614-9731 0009-0000-8399-7798 0000-0001-6733-6332 |
OpenAccessLink | https://doaj.org/article/aa4a3ff88cdf452889f72244576a9070 |
PMID | 38569631 |
PQID | 3033009385 |
PQPubID | 23479 |
PageCount | 11 |
ParticipantIDs | nrf_kci_oai_kci_go_kr_ARTI_10418365 doaj_primary_oai_doaj_org_article_aa4a3ff88cdf452889f72244576a9070 pubmedcentral_primary_oai_pubmedcentral_nih_gov_10992652 proquest_miscellaneous_3033009385 pubmed_primary_38569631 crossref_primary_10_14245_ns_2347326_663 crossref_citationtrail_10_14245_ns_2347326_663 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2024-03-01 |
PublicationDateYYYYMMDD | 2024-03-01 |
PublicationDate_xml | – month: 03 year: 2024 text: 2024-03-01 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | Korea (South) |
PublicationPlace_xml | – name: Korea (South) |
PublicationTitle | Neurospine |
PublicationTitleAlternate | Neurospine |
PublicationYear | 2024 |
Publisher | Korean Spinal Neurosurgery Society 대한척추신경외과학회 |
Publisher_xml | – name: Korean Spinal Neurosurgery Society – name: 대한척추신경외과학회 |
References | ref13 ref12 ref15 ref20 ref11 ref10 ref21 ref2 ref1 ref17 Hosono (ref14) 2010 ref16 ref19 ref18 ref8 ref7 ref9 ref4 ref3 ref6 ref5 40625020 - Neurospine. 2025 Jun;22(2):613-614. doi: 10.14245/ns.2550126.063. |
References_xml | – ident: ref2 doi: 10.1007/s00586-022-07349-x – ident: ref12 doi: 10.21037/atm.2016.08.57 – ident: ref5 doi: 10.1097/brs.0000000000004243 – ident: ref20 doi: 10.1097/brs.0000000000001849 – ident: ref6 doi: 10.1007/s00586-017-4949-2 – ident: ref7 doi: 10.1007/s00586-017-4948-3 – ident: ref3 doi: 10.1302/0301-620x.69b2.3818752 – ident: ref17 doi: 10.1097/01.brs.0000190452.33258.72 – ident: ref4 doi: 10.1302/0301-620x.90b9.20459 – ident: ref18 doi: 10.1155/2018/5138234 – ident: ref19 doi: 10.1093/neuros/nyz499 – ident: ref10 doi: 10.1109/jbhi.2022.3184870 – ident: ref15 doi: 10.1016/j.apmr.2004.01.037 – ident: ref21 doi: 10.1007/s00776-013-0381-6 – ident: ref13 doi: 10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 – ident: ref16 doi: 10.1097/01.bsd.0000203275.97627.9f – ident: ref9 doi: 10.1177/20552076231179030 – start-page: E273 volume-title: Myelopathy hand: New evidence of the classical sign year: 2010 ident: ref14 – ident: ref1 doi: 10.1177/1073858412467377 – ident: ref8 doi: 10.1097/brs.0000000000003696 – ident: ref11 doi: 10.1016/j.clineuro.2019.105414 – reference: 40625020 - Neurospine. 2025 Jun;22(2):613-614. doi: 10.14245/ns.2550126.063. |
SSID | ssib044754331 ssj0002002413 |
Score | 2.2631552 |
Snippet | Objective: Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release... Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R)... Objective Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release... |
SourceID | nrf doaj pubmedcentral proquest pubmed crossref |
SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
StartPage | 46 |
SubjectTerms | 10-second grip and release test deep learning degenerative cervical myelopathy diagnostic performance Original shortened assessment duration 신경외과학 |
Title | Deep Learning-Enhanced Hand Grip and Release Test for Degenerative Cervical Myelopathy: Shortening Assessment Duration to 6 Seconds |
URI | https://www.ncbi.nlm.nih.gov/pubmed/38569631 https://www.proquest.com/docview/3033009385 https://pubmed.ncbi.nlm.nih.gov/PMC10992652 https://doaj.org/article/aa4a3ff88cdf452889f72244576a9070 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART003067418 |
Volume | 21 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
ispartofPNX | Neurospine, 2024, 21(1), , pp.46-56 |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lb9QwELZQT1wQiFd4yQgOXNJuEj8SbqW7ZUEqB9pKvVmOY-9WrbLVPg69cOGP842TRrsIxIXLZpU4zxnPfF88-czYe5FlvrBgJyGEUSoAQNJaa5dWspGNqmutXKy2-Kam5-LrhbzYmuqLasI6eeDuwR1YK2wRQlm6JgiZl2UVNNKOAE62IHaRrSPnbZEpeBKp2NGnQMPbFipFEHGu5FyWKkXaLXqdHxr5O4B980JoQJl9pYqdFBWV_JF42mX4Ewj9vZZyKzkdP2QPelTJD7u7ecTu-fYx-zn2_ob3AqqzdNLO42g_n9q24Z8RLDj9-Y68g0zGz3A-DgTLx34WpagpDvKjGEpw6JNbqi0CXLz9yE_nVKFLB-WHg7AnH286Z-LrBVf8lIh2s3rCzo8nZ0fTtJ9zIXWgSmvQyVrXrm5CkzkQTF1ljjBGqKxuCuUU4Ia1FYmo-UIKlWVWO1vZWslAyvm2eMr22kXrnzNeVjr3ta5kHoJo7KiEX4BPVhIgrXIjlbD9u8dsXC9ITvNiXBsiJmQX065MbxcDuyTsw7DDTafF8femn8huQzMS0Y4r4Fqmdy3zL9dK2DtY3Vy5y7g_LWcLc7U0oBpfcGaBcKhkwt7eeYVB16TxFtv6xWZlgA4KemNUos2zzkuGC8JKhdiXJazc8Z-dK97d0l7Oo_w3jWXmSuYv_sc9vmT3c3SNrqruFdtbLzf-NWDWun4TexR-T35MfgFL8iD0 |
linkProvider | Directory of Open Access Journals |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Deep+Learning-Enhanced+Hand+Grip+and+Release+Test+for+Degenerative+Cervical+Myelopathy%3A+Shortening+Assessment+Duration+to+6+Seconds&rft.jtitle=Neurospine&rft.au=Ye%2C+Yongyu&rft.au=Chang%2C+Yunbing&rft.au=Wu%2C+Weihao&rft.au=Liao%2C+Tianying&rft.date=2024-03-01&rft.issn=2586-6583&rft.volume=21&rft.issue=1&rft.spage=46&rft_id=info:doi/10.14245%2Fns.2347326.663&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2586-6583&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2586-6583&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2586-6583&client=summon |