2019 Computing in Cardiology (CinC)最新文献_第4页

Ring-Topology Echo State Networks for ICU Sepsis Classification 环状拓扑回声状态网络用于ICU脓毒症分类

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005810

M. Alfaras, Rui Varandas, H. Gamboa

引用次数: 4

Evaluation of Short-Term Pacing Effect to Predict Long-Term Response to Cardiac Resynchronization Therapy: the TRAJECTORIES Study 评估短期起搏效果以预测心脏再同步化治疗的长期反应:轨迹研究

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005678

G. Santarelli, Roberta Ciccotelli, G. Molon, F. Zanon, A. Corzani, A. Rossillo, M. Biffi, G. Zanotto, L. Lanzoni, S. Severi, C. Tomasi, C. Corsi

{"title":"Evaluation of Short-Term Pacing Effect to Predict Long-Term Response to Cardiac Resynchronization Therapy: the TRAJECTORIES Study","authors":"G. Santarelli, Roberta Ciccotelli, G. Molon, F. Zanon, A. Corzani, A. Rossillo, M. Biffi, G. Zanotto, L. Lanzoni, S. Severi, C. Tomasi, C. Corsi","doi":"10.23919/CinC49843.2019.9005678","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005678","url":null,"abstract":"Cardiac resynchronization therapy (CRT) is an effective treatment for chronic symptomatic systolic heart failure with cardiac dyssynchrony, but about 1/3 of patients do not respond favorably to the therapy. We hypothesized that acute modifications of the coronary sinus (CS) pacing cathode movements induced by biventricular pacing may be related to resynchronization process and consequently may carry predictive power on CRT response. A method for the 3D reconstruction of CS lead’s pacing cathode trajectory (3DTJ) throughout a cardiac cycle showed that trajectory’s geometry suddenly changed in responders (R) upon starting of biventricular pacing, becoming less eccentric and more multi-directional. Our multicenter observational study aimed at evaluating the clinical value of 3DTJ. Out of 119 patients enrolled, 50 have ended follow-up and have been analyzed. Concordance between 3DTJ metrics and response was 82% overall (41/50), 91% in R (31/34), 62% in NR (10/16). The proposed 3DTJ metric showed high sensitivity (91%) with specificity=62%; PPV=84%, NPV=77%. From our data, 3DTJ seems a promising tool to acutely predict CS pacing site-specific response to CRT. Its investigational use as an intra-operatory, real-time guidance for selecting LV pacing sites may open new opportunities for CRT patients’ selection and therapy delivery.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"451 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79702803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Factors Influencing Automated Limited Lead Detection of Atrial Fibrillation 影响心房颤动自动有限导联检测的因素

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005768

P. Macfarlane, S. Latif, B. Devine

{"title":"Factors Influencing Automated Limited Lead Detection of Atrial Fibrillation","authors":"P. Macfarlane, S. Latif, B. Devine","doi":"10.23919/CinC49843.2019.9005768","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005768","url":null,"abstract":"There has been interest relating to automated analysis of a lead I ECG to detect cardiac arrhythmias. Little interest has been shown in the accuracy of using lead I as opposed to 6 limb leads or the full 12 lead ECG. The aim of this small study was to assess the efficacy of using only lead I but also to look at the effect of analysing a single 30s recording as a continuous recording versus five 10s overlapping recordings constituting a 30s record.One hundred 10s digital 12 lead ECGs with atrial fibrillation (AF) were used. Chest leads were removed and the 6 limb leads then used for analysis of rhythm. Similarly, lead I alone was used. Separately 100 single lead I ECGs classified as AF in the PhysioNet 2017 database were analysed, both as single 30s recordings and as five 10s ECGs commencing at 0, 5, 10, 15 and 20s from the start of the recording. An algorithm made the diagnosis from 5 reports. All analyses were made with the Glasgow Program. For the 10s 12 lead ECGs, 96% were reported as AF using 6 limb leads and 93% using lead I. For the 30s recordings, 92% were reported as AF using a single 30s analysis and 91% as AF using the five ECGs.In conclusion, one lead and 6 leads are not as sensitive as 12 leads in detecting AF, while five 10s reports combined are no more sensitive than a single 30s report though more specific.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"38 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83862380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Graphical Evaluation Tool to Utilize ECG Data Without Reference Annotation 一种利用心电图数据的无参考注释的图形化评估工具

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005552

Yu-He Zhang, S. Babaeizadeh

{"title":"A Graphical Evaluation Tool to Utilize ECG Data Without Reference Annotation","authors":"Yu-He Zhang, S. Babaeizadeh","doi":"10.23919/CinC49843.2019.9005552","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005552","url":null,"abstract":"Without reference annotation, statistical metrics such as sensitivity and positive predictive value (PPV) cannot be calculated. Annotating a large ECG database may not be feasible, hence, the interest in developing an evaluation tool that does not require reference annotation. We developed a tool for evaluating key performance attributes (KPA) including arrhythmia detection, heart rate, ST value, and noise tolerance. The tool has three layers of KPA graphics. The top layer includes interactive distribution graphs of the KPA values for aggregated results for the entire database. From this top layer the user can select an individual record to launch interactive trending graphs that display the KPA values, or their discrepancies, for a time span on that particular record. From this second layer the user can identify any KPA value of interest (e.g., a specific arrhythmia label) to view the underlying ECG waveform. Navigating through these three layers, the user is able to quickly confirm the validity of KPA reported by the algorithm. We modified the noise tolerance of an exercise ECG arrhythmia algorithm. Then used this tool to visually verify the resulting improvement on the Telemetric and Holter ECG Warehouse (THEW) stress database E-OTH-12-0927-015. We confirmed the visual verification of improvement by manually annotating a small subset of records in this database.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"27 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81008391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Representation Learning for Early Sepsis Prediction 表征学习用于脓毒症早期预测

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005565

Luan Tran, M. Nguyen, C. Shahabi

引用次数: 1

Local Atrial Conduction Velocity During Pacing as Indication of Atrial Fibrillation Substrate Complexity 起搏时局部心房传导速度作为心房颤动底物复杂性的指示

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005605

Frank van Rosmalen, L. Pison, T. Delhaas, H. Crijns, S. Zeemering, U. Schotten

{"title":"Local Atrial Conduction Velocity During Pacing as Indication of Atrial Fibrillation Substrate Complexity","authors":"Frank van Rosmalen, L. Pison, T. Delhaas, H. Crijns, S. Zeemering, U. Schotten","doi":"10.23919/CinC49843.2019.9005605","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005605","url":null,"abstract":"Background: Pulmonary vein isolation (PVI) as treatment for atrial fibrillation (AF) is not effective in up to 60% of patients with persistent AF; AF drivers outside of the pulmonary veins can contribute to AF recurrences after PVI. In this study we explored the potential use of local conduction velocity (CV) during pacing as a marker of left atrial (LA) substrate complexity.Methods: LA activation times were recorded for 7 AF patients during coronary sinus (CS) pacing before PVI using a Pentaray catheter. Activation times were relative to the CS pacing spike. LA activation locations were triangularized to calculate CV: the local direction and speed of the activation wave front. CV was quantified by the total CV distribution.Results: A mean of 1622 CVs were calculated per patient. Distribution of CVs showed a similar morphology, with median CVs in the range [0.26, 0.36] and interquartile ranges in the range [0.29, 0.39].Conclusion: This study shows that although it is feasible to calculate CVs based on sequential CARTO mapping of the LA during CS pacing, the resulting distribution of CVs using this procedure is not necessarily able to identify substrate complexity because of the large similarity between distributions and the relatively small differences in medians.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"38 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89655333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Atrial Fibrillation Detection from PPG Interbeat Intervals via a Recurrent Neural Network 基于循环神经网络的PPG间隔房颤检测

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005767

J. V. Zaen, Elsa Genzoni, F. Braun, P. Renevey, E. Pruvot, J. Vesin, M. Lemay

引用次数: 1

Improving the Performance of a Neural Network for Early Prediction of Sepsis 改进脓毒症早期预测的神经网络性能

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005754

ByeongTak Lee, Kyung-Jae Cho, Oyeon Kwon, Yeha Lee

{"title":"Improving the Performance of a Neural Network for Early Prediction of Sepsis","authors":"ByeongTak Lee, Kyung-Jae Cho, Oyeon Kwon, Yeha Lee","doi":"10.23919/CinC49843.2019.9005754","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005754","url":null,"abstract":"Early prediction of sepsis is a clinically important, yet remains challenging. As machine learning develops, there have been many approaches for prediction of sepsis using neural network-based models. In this work, We propose various methods including feature engineering, regularization technique, and train data sampling methods, which can boost the performance of the model. Our approach consist of three-component: a feature engineering, an auxiliary loss, and a manipulation of training distribution. In feature engineering, we employed a novel input imputation method that combines input decay, masking, and duration of missing and input transformation. As for regularization, we used the reconstruction error as the auxiliary loss. Meanwhile, we manipulated the distribution of training sample using normal point re-sampling and population-based sampling. On the validation set, our approach improved the performance of LSTM as AUROC/AUPRC of 0. 045/0.017, and the performance of transformer is enhanced AUROC/AUPRC of 0.034/0.024. Finally, we submitted our transformer trained with proposed method on the official test set and obtained the utility score of 0.291 (Team name:vn, Rank:23).","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"22 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87442264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Efficient Instantaneous ECG Delineation Algorithm 一种高效的瞬时心电圈定算法

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005708

Thion Ming Chieng, Y. Hau, Z. Omar, Chiao Wen Lim

{"title":"An Efficient Instantaneous ECG Delineation Algorithm","authors":"Thion Ming Chieng, Y. Hau, Z. Omar, Chiao Wen Lim","doi":"10.23919/CinC49843.2019.9005708","DOIUrl":"https://doi.org/10.23919/CinC49843.2019.9005708","url":null,"abstract":"An efficient electrocardiogram (ECG) delineation algorithm is proposed to instantaneously delineate the ECG characteristic points, such as peak, onset and offset points of QRS, P and T waves. It is essential to delineate the ECG characteristic waves accurately and precisely as it ensure the performance of ECG analysis and diagnosis. The proposed delineation algorithm is based on discrete wavelet transform (DWT) and moving window average (MWA) techniques. The proposed delineation algorithm is evaluated and assessed with the annotation data of QT database in term of accuracy, sensitivity and positive predictive value. With the only available 13 sets QT database records with modified Lead II data, the proposed algorithm achieved significant P peak, R peak, T peak and T offset delineation performance with the accuracy of 95.34%, 99.80%, 90.82% and 86.33% respectively when evaluated with q1c annotation file. The mean difference between detected and annotated T offset based on q1c and q2c is 13 ms and 3.6 ms respectively. The delineation of 15 minute-long ECG record only required 74.702 second. As conclusion, the proposed ECG delineation algorithm based on DWT and MWA techniques have been proven simple, efficient and accurate in delineating the significant ECG characteristic points.","PeriodicalId":6697,"journal":{"name":"2019 Computing in Cardiology (CinC)","volume":"46 1","pages":"Page 1-Page 4"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80009459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

U-Net Architecture for the Automatic Detection and Delineation of the Electrocardiogram 用于心电图自动检测和描绘的U-Net体系结构

2019 Computing in Cardiology (CinC) Pub Date : 2019-09-01 DOI: 10.23919/CinC49843.2019.9005824

G. Jiménez-Pérez, A. Alcaine, O. Camara

引用次数: 18