دورية أكاديمية
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Deep learning‐based identification of sinoatrial node‐like pacemaker cells from SHOX2/HCN4 double‐positive cells differentiated from human iPS cells

التفاصيل البيبلوغرافية
العنوان: Deep learning‐based identification of sinoatrial node‐like pacemaker cells from SHOX2/HCN4 double‐positive cells differentiated from human iPS cells
المؤلفون: Takayuki Wakimizu, Junpei Naito, Manabu Ishida, Yasutaka Kurata, Motokazu Tsuneto, Yasuaki Shirayoshi, Ichiro Hisatome
المصدر: Journal of Arrhythmia, Vol 39, Iss 4, Pp 664-668 (2023)
بيانات النشر: Wiley, 2023.
سنة النشر: 2023
المجموعة: LCC:Diseases of the circulatory (Cardiovascular) system
مصطلحات موضوعية: automaticity, CNN model, deep learning, human iPS cells, SAN‐like cells, Diseases of the circulatory (Cardiovascular) system, RC666-701
الوصف: Abstract Background Cardiomyocytes derived from human iPS cells (hiPSCs) include cells showing SAN‐ and non‐SAN‐type spontaneous APs. Objectives To examine whether the deep learning technology could identify hiPSC‐derived SAN‐like cells showing SAN‐type‐APs by their shape. Methods We acquired phase‐contrast images for hiPSC‐derived SHOX2/HCN4 double‐positive SAN‐like and non‐SAN‐like cells and made a VGG16‐based CNN model to classify an input image as SAN‐like or non‐SAN‐like cell, compared to human discriminability. Results All parameter values such as accuracy, recall, specificity, and precision obtained from the trained CNN model were higher than those of human classification. Conclusions Deep learning technology could identify hiPSC‐derived SAN‐like cells with considerable accuracy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1883-2148
1880-4276
العلاقة: https://doaj.org/toc/1880-4276Test; https://doaj.org/toc/1883-2148Test
DOI: 10.1002/joa3.12883
الوصول الحر: https://doaj.org/article/dbf7b7edc7db441ea0cd27e9a6940e7eTest
رقم الانضمام: edsdoj.bf7b7edc7db441ea0cd27e9a6940e7e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:18832148
18804276
DOI:10.1002/joa3.12883