Behar JA - Search Results

1

Atrial fibrillation risk prediction from the 12-lead electrocardiogram using digital biomarkers and deep representation learning.

Biton S, Gendelman S, Ribeiro AH, Miana G, Moreira C, Ribeiro ALP, Behar JA. Biton S, et al. Among authors: behar ja. Eur Heart J Digit Health. 2021 Aug 5;2(4):576-585. doi: 10.1093/ehjdh/ztab071. eCollection 2021 Dec. Eur Heart J Digit Health. 2021. PMID: 36713102 Free PMC article.

2

Remote Atrial Fibrillation Burden Estimation Using Deep Recurrent Neural Network.

Chocron A, Oster J, Biton S, Mandel F, Elbaz M, Zeevi YY, Behar JA. Chocron A, et al. Among authors: behar ja. IEEE Trans Biomed Eng. 2021 Aug;68(8):2447-2455. doi: 10.1109/TBME.2020.3042646. Epub 2021 Jul 16. IEEE Trans Biomed Eng. 2021. PMID: 33275575

3

Effect of temporal resolution on the detection of cardiac arrhythmias using HRV features and machine learning.

Ben Itzhak S, Ricon SS, Biton S, Behar JA, Sobel JA. Ben Itzhak S, et al. Among authors: behar ja. Physiol Meas. 2022 Apr 28;43(4). doi: 10.1088/1361-6579/ac6561. Physiol Meas. 2022. PMID: 35506573

4

Generalizable and robust deep learning algorithm for atrial fibrillation diagnosis across geography, ages and sexes.

Biton S, Aldhafeeri M, Marcusohn E, Tsutsui K, Szwagier T, Elias A, Oster J, Sellal JM, Suleiman M, Behar JA. Biton S, et al. Among authors: behar ja. NPJ Digit Med. 2023 Mar 17;6(1):44. doi: 10.1038/s41746-023-00791-1. NPJ Digit Med. 2023. PMID: 36932150 Free PMC article.

5

An artificial intelligence-enabled Holter algorithm to identify patients with ventricular tachycardia by analysing their electrocardiogram during sinus rhythm.

Gendelman S, Zvuloni E, Oster J, Suleiman M, Derman R, Behar JA. Gendelman S, et al. Among authors: behar ja. Eur Heart J Digit Health. 2024 Apr 3;5(4):409-415. doi: 10.1093/ehjdh/ztae025. eCollection 2024 Jul. Eur Heart J Digit Health. 2024. PMID: 39081947 Free PMC article.

6

Machine learning for nocturnal mass diagnosis of atrial fibrillation in a population at risk of sleep-disordered breathing.

Chocron A, Efraim R, Mandel F, Rueschman M, Palmius N, Penzel T, Elbaz M, Behar JA. Chocron A, et al. Among authors: behar ja. Physiol Meas. 2020 Nov 6;41(10):104001. doi: 10.1088/1361-6579/abb8bf. Physiol Meas. 2020. PMID: 32932240

7

Machine learning for nocturnal diagnosis of chronic obstructive pulmonary disease using digital oximetry biomarkers.

Levy J, Álvarez D, Del Campo F, Behar JA. Levy J, et al. Among authors: behar ja. Physiol Meas. 2021 Jun 17;42(5). doi: 10.1088/1361-6579/abf5ad. Physiol Meas. 2021. PMID: 33827067

8

Positional sleep apnea phenotyping using machine learning and digital oximetry biomarkers.

Ben Sason Y, Levy J, Oksenberg A, Sobel J, Behar JA. Ben Sason Y, et al. Among authors: behar ja. Physiol Meas. 2023 Aug 3;44(8). doi: 10.1088/1361-6579/accefc. Physiol Meas. 2023. PMID: 37080233

9

Digital oximetry biomarkers for assessing respiratory function: standards of measurement, physiological interpretation, and clinical use.

Levy J, Álvarez D, Rosenberg AA, Alexandrovich A, Del Campo F, Behar JA. Levy J, et al. Among authors: behar ja. NPJ Digit Med. 2021 Jan 4;4(1):1. doi: 10.1038/s41746-020-00373-5. NPJ Digit Med. 2021. PMID: 33398041 Free PMC article.

10

Predict alone, decide together: cardiac abnormality detection based on single lead classifier voting.

Aublin PG, Ben Ammar M, Fix J, Barret M, Behar JA, Oster J. Aublin PG, et al. Among authors: behar ja. Physiol Meas. 2022 May 25;43(5). doi: 10.1088/1361-6579/ac66b9. Physiol Meas. 2022. PMID: 35413703

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