Using neural networks for image analysis in general physiology.

IF 3.3 2区 医学 Q1 PHYSIOLOGY Journal of General Physiology Pub Date : 2024-09-17 DOI:10.1085/jgp.202413623
Eduardo Rios
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Abstract

An article with three goals, namely, to (1) provide the set of ideas and information needed to understand, at a basic level, the application of convolutional neural networks (CNNs) to analyze images in biology; (2) trace a path to adopting and adapting, at code level, the applications of machine learning (ML) that are freely available and potentially applicable in biology research; (3) by using as examples the networks described in the recent article by Ríos et al. (2024. https://doi.org/10.1085/jgp.202413595), add logic and clarity to their description.
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利用神经网络进行普通生理学图像分析。
这篇文章有三个目标,即:(1) 提供一套所需的观点和信息,以便从根本上理解卷积神经网络 (CNN) 在生物学图像分析中的应用;(2) 在代码层面上追溯采用和调整机器学习 (ML) 应用的路径,这些应用可免费获得,并可能适用于生物学研究;(3) 以里奥斯等人最近发表的文章 (2024. https://doi.org/10.1085/jgp.202413595) 中描述的网络为例,增加其描述的逻辑性和清晰度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
10.50%
发文量
88
审稿时长
6-12 weeks
期刊介绍: General physiology is the study of biological mechanisms through analytical investigations, which decipher the molecular and cellular mechanisms underlying biological function at all levels of organization. The mission of Journal of General Physiology (JGP) is to publish mechanistic and quantitative molecular and cellular physiology of the highest quality, to provide a best-in-class author experience, and to nurture future generations of independent researchers. The major emphasis is on physiological problems at the cellular and molecular level.
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