JP2022535574A - トルサード・ド・ポワントのリスクを検出するための方法 - Google Patents

トルサード・ド・ポワントのリスクを検出するための方法 Download PDF

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JP2022535574A
JP2022535574A JP2021572374A JP2021572374A JP2022535574A JP 2022535574 A JP2022535574 A JP 2022535574A JP 2021572374 A JP2021572374 A JP 2021572374A JP 2021572374 A JP2021572374 A JP 2021572374A JP 2022535574 A JP2022535574 A JP 2022535574A
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ecg
risk
data
machine learning
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JP2022535574A5 (https=
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ジョー－エリー セラム
エディ プリフティ
アルフレード アラム プリーニ
ジャン－ダニエル ザッカー
クリスチャン ファンク－ブレンターノ
アントワーヌ レーナルト
イザベル ダンジョワ
ファブリス エクストラミアナ
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Sorbonne Universite
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
JP2021572374A 2019-06-05 2020-06-04 トルサード・ド・ポワントのリスクを検出するための方法 Pending JP2022535574A (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP19305730.4 2019-06-05
EP19305730.4A EP3748647A1 (en) 2019-06-05 2019-06-05 Method for detecting risk of torsades de pointes
PCT/EP2020/065562 WO2020245322A1 (en) 2019-06-05 2020-06-04 Method for detecting risk of torsades de pointes

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JP2022535574A true JP2022535574A (ja) 2022-08-09
JP2022535574A5 JP2022535574A5 (https=) 2023-06-05

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JP2021572374A Pending JP2022535574A (ja) 2019-06-05 2020-06-04 トルサード・ド・ポワントのリスクを検出するための方法

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US (1) US20220230758A1 (https=)
EP (2) EP3748647A1 (https=)
JP (1) JP2022535574A (https=)
CN (1) CN113994437A (https=)
CA (1) CA3142552A1 (https=)
WO (1) WO2020245322A1 (https=)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024533041A (ja) * 2022-08-18 2024-09-12 メディカル・エーアイ・カンパニー・リミテッド 複数の心電図を用いたディープラーニングに基づく健康状態予測システム
JP2025126288A (ja) * 2023-08-22 2025-08-28 シナジー エーアイ カンパニー リミテッド 心臓疾患予測のためのディープラーニングモデル学習方法

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102362678B1 (ko) * 2021-06-02 2022-02-14 주식회사 뷰노 생체신호 분석 방법
WO2023057200A1 (en) * 2021-10-04 2023-04-13 Biotronik Se & Co. Kg Computer implemented method for determining a medical parameter, training method and system
KR102653258B1 (ko) * 2022-02-18 2024-04-01 주식회사 뷰노 심전도 기술 및 결과 통합 방법
CN116269417B (zh) * 2023-03-30 2025-05-16 中山大学孙逸仙纪念医院 建立scd风险预测模型的方法、装置、电子设备及介质
WO2025010429A1 (en) * 2023-07-06 2025-01-09 The General Hospital Corporation Method and apparatus for evaluating cardiac function
EP4497386A1 (en) 2023-07-28 2025-01-29 Assistance Publique - Hôpitaux de Paris Method for detecting risk of torsades de pointes in long qt patients

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007514488A (ja) * 2003-12-19 2007-06-07 アールボルウ ウニベーシテット 長ｑｔ症候群における心電図湾曲および薬品の影響を分析するためのシステムおよび方法
US20080082016A1 (en) * 2006-10-03 2008-04-03 Mark Kohls System and method of serial comparison for detection of long qt syndrome (lqts)
JP2018503885A (ja) * 2014-11-14 2018-02-08 ゾール メディカル コーポレイションＺＯＬＬ Ｍｅｄｉｃａｌ Ｃｏｒｐｏｒａｔｉｏｎ 医療前兆イベント予測
US20180263585A1 (en) * 2017-03-17 2018-09-20 Siemens Healthcare Gmbh Source of abdominal pain identification in medical imaging
US20190059764A1 (en) * 2016-04-13 2019-02-28 Assistance Publique - Hopitaux De Paris Method for determining the likelihood of torsades de pointes being induced

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2006124788A2 (en) * 2005-05-13 2006-11-23 Cardiocore Lab, Inc. Method and apparatus for rapid interpretive analysis of electrocardiographic waveforms
US8529448B2 (en) * 2009-12-31 2013-09-10 Cerner Innovation, Inc. Computerized systems and methods for stability—theoretic prediction and prevention of falls
US8437839B2 (en) * 2011-04-12 2013-05-07 University Of Utah Research Foundation Electrocardiographic assessment of arrhythmia risk
US9408543B1 (en) * 2012-08-17 2016-08-09 Analytics For Life Non-invasive method and system for characterizing cardiovascular systems for all-cause mortality and sudden cardiac death risk
EP2896428B1 (fr) * 2014-01-16 2016-11-09 Sorin CRM SAS Ensemble de réseau de neurones pour l'évaluation et l'adaptation d'une thérapie antitachycardique par un défibrillateur implantable
US10517494B2 (en) * 2014-11-14 2019-12-31 Beth Israel Deaconess Medical Center, Inc. Method and system to access inapparent conduction abnormalities to identify risk of ventricular tachycardia
EP3318184B1 (en) * 2016-11-08 2024-01-10 Heart2Save Oy System for determining a probability for a person to have arrhythmia

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007514488A (ja) * 2003-12-19 2007-06-07 アールボルウ ウニベーシテット 長ｑｔ症候群における心電図湾曲および薬品の影響を分析するためのシステムおよび方法
US20080082016A1 (en) * 2006-10-03 2008-04-03 Mark Kohls System and method of serial comparison for detection of long qt syndrome (lqts)
JP2018503885A (ja) * 2014-11-14 2018-02-08 ゾール メディカル コーポレイションＺＯＬＬ Ｍｅｄｉｃａｌ Ｃｏｒｐｏｒａｔｉｏｎ 医療前兆イベント予測
US20190059764A1 (en) * 2016-04-13 2019-02-28 Assistance Publique - Hopitaux De Paris Method for determining the likelihood of torsades de pointes being induced
US20180263585A1 (en) * 2017-03-17 2018-09-20 Siemens Healthcare Gmbh Source of abdominal pain identification in medical imaging

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ATTIA, ZACHI I., ET AL.: "Noninvative assessment of dofetilide plasma concentration using a deep learning (neural network) ana", PLOS ONE, vol. 13, no. 8, JPN7024001828, 22 August 2018 (2018-08-22), pages 0201059, ISSN: 0005491779 *
YILDIRIM, OZAL ET AL.: "Arrhythmia detection using deep convolutional neural network with long duration ECG signals", COMPUTERS IN BIOLOGY AND MEDICINE, vol. 102, JPN7024001827, 12 September 2018 (2018-09-12), pages 411 - 420, ISSN: 0005491778 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2024533041A (ja) * 2022-08-18 2024-09-12 メディカル・エーアイ・カンパニー・リミテッド 複数の心電図を用いたディープラーニングに基づく健康状態予測システム
JP2025126288A (ja) * 2023-08-22 2025-08-28 シナジー エーアイ カンパニー リミテッド 心臓疾患予測のためのディープラーニングモデル学習方法
JP7837100B2 (ja) 2023-08-22 2026-03-30 シナジー エーアイ カンパニー リミテッド 心臓疾患予測のためのディープラーニングモデル学習方法

Also Published As

Publication number Publication date
CN113994437A (zh) 2022-01-28
EP3981011A1 (en) 2022-04-13
WO2020245322A1 (en) 2020-12-10
EP3748647A1 (en) 2020-12-09
CA3142552A1 (en) 2020-12-10
US20220230758A1 (en) 2022-07-21

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