[Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm].
Saved in:
| Title: | [Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm]. |
|---|---|
| Authors: | Chernina VY; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow., Pisov ME; Skolkovo Institute of Science and Technology, Moscow., Belyaev MG; Skolkovo Institute of Science and Technology, Moscow., Bekk IV; National Medical and Surgical Center named after N.I. Pirogov of the Ministry of Healthcare of the Russian Federation, Moscow., Zamyatina KA; A.V. Vishnevsky National Medical Research Center of Surgery, Moscow., Korb TA; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow., Aleshina OO; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow., Shukina EA; Moscow State University of Medicine and Dentistry named after A.I. Evdokimov, Moscow., Solovev AV; Sklifosovsky Clinical and Research Institute for Emergency Medicine, Moscow., Skvortsov RA; National Medical and Surgical Center named after N.I. Pirogov of the Ministry of Healthcare of the Russian Federation, Moscow., Filatova DA; Lomonosov Moscow State University, Moscow., Sitdikov DI; The First Sechenov Moscow State Medical University, Moscow., Chesnokova AO; The First Sechenov Moscow State Medical University, Moscow., Morozov SP; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow., Gombolevsky VA; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow. |
| Source: | Kardiologiia [Kardiologiia] 2020 Oct 14; Vol. 60 (9), pp. 46-54. Date of Electronic Publication: 2020 Oct 14. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: OOO Obshchestvo spet︠s︡ialistov po serdechnoĭ nedostatochnosti Country of Publication: Russia (Federation) NLM ID: 0376351 Publication Model: Electronic Cited Medium: Print ISSN: 0022-9040 (Print) Linking ISSN: 00229040 NLM ISO Abbreviation: Kardiologiia Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 33131474 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: [Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm]. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Chernina+VY%22">Chernina VY</searchLink>; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow.<br /><searchLink fieldCode="AU" term="%22Pisov+ME%22">Pisov ME</searchLink>; Skolkovo Institute of Science and Technology, Moscow.<br /><searchLink fieldCode="AU" term="%22Belyaev+MG%22">Belyaev MG</searchLink>; Skolkovo Institute of Science and Technology, Moscow.<br /><searchLink fieldCode="AU" term="%22Bekk+IV%22">Bekk IV</searchLink>; National Medical and Surgical Center named after N.I. Pirogov of the Ministry of Healthcare of the Russian Federation, Moscow.<br /><searchLink fieldCode="AU" term="%22Zamyatina+KA%22">Zamyatina KA</searchLink>; A.V. Vishnevsky National Medical Research Center of Surgery, Moscow.<br /><searchLink fieldCode="AU" term="%22Korb+TA%22">Korb TA</searchLink>; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow.<br /><searchLink fieldCode="AU" term="%22Aleshina+OO%22">Aleshina OO</searchLink>; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow.<br /><searchLink fieldCode="AU" term="%22Shukina+EA%22">Shukina EA</searchLink>; Moscow State University of Medicine and Dentistry named after A.I. Evdokimov, Moscow.<br /><searchLink fieldCode="AU" term="%22Solovev+AV%22">Solovev AV</searchLink>; Sklifosovsky Clinical and Research Institute for Emergency Medicine, Moscow.<br /><searchLink fieldCode="AU" term="%22Skvortsov+RA%22">Skvortsov RA</searchLink>; National Medical and Surgical Center named after N.I. Pirogov of the Ministry of Healthcare of the Russian Federation, Moscow.<br /><searchLink fieldCode="AU" term="%22Filatova+DA%22">Filatova DA</searchLink>; Lomonosov Moscow State University, Moscow.<br /><searchLink fieldCode="AU" term="%22Sitdikov+DI%22">Sitdikov DI</searchLink>; The First Sechenov Moscow State Medical University, Moscow.<br /><searchLink fieldCode="AU" term="%22Chesnokova+AO%22">Chesnokova AO</searchLink>; The First Sechenov Moscow State Medical University, Moscow.<br /><searchLink fieldCode="AU" term="%22Morozov+SP%22">Morozov SP</searchLink>; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow.<br /><searchLink fieldCode="AU" term="%22Gombolevsky+VA%22">Gombolevsky VA</searchLink>; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Moscow. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%220376351%22">Kardiologiia</searchLink> [Kardiologiia] 2020 Oct 14; Vol. 60 (9), pp. 46-54. <i>Date of Electronic Publication: </i>2020 Oct 14. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22OOO+Obshchestvo+spet︠s︡ialistov+po+serdechnoĭ+nedostatochnosti%22">OOO Obshchestvo spet︠s︡ialistov po serdechnoĭ nedostatochnosti </searchLink><i>Country of Publication: </i>Russia (Federation) <i>NLM ID: </i>0376351 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>0022-9040 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200229040%22">00229040 </searchLink><i>NLM ISO Abbreviation: </i>Kardiologiia <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=33131474 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.18087/cardio.2020.9.n1111 Languages: – Code: rus Text: Russian PhysicalDescription: Pagination: StartPage: 46 Titles: – TitleFull: [Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm]. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chernina VY – PersonEntity: Name: NameFull: Pisov ME – PersonEntity: Name: NameFull: Belyaev MG – PersonEntity: Name: NameFull: Bekk IV – PersonEntity: Name: NameFull: Zamyatina KA – PersonEntity: Name: NameFull: Korb TA – PersonEntity: Name: NameFull: Aleshina OO – PersonEntity: Name: NameFull: Shukina EA – PersonEntity: Name: NameFull: Solovev AV – PersonEntity: Name: NameFull: Skvortsov RA – PersonEntity: Name: NameFull: Filatova DA – PersonEntity: Name: NameFull: Sitdikov DI – PersonEntity: Name: NameFull: Chesnokova AO – PersonEntity: Name: NameFull: Morozov SP – PersonEntity: Name: NameFull: Gombolevsky VA IsPartOfRelationships: – BibEntity: Dates: – D: 14 M: 10 Text: 2020 Oct 14 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 0022-9040 Numbering: – Type: volume Value: 60 – Type: issue Value: 9 Titles: – TitleFull: Kardiologiia Type: main |
| ResultId | 1 |