AI-empowered visualization of nucleic acid testing

IF 5.2 2区医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL

Life sciences Pub Date : 2024-10-31 DOI:10.1016/j.lfs.2024.123209

Zehua Lu, Xiaogang Wang, Junge Chen

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引用次数: 0

Abstract

Aims

The visualization of nucleic acid testing (NAT) results plays a critical role in diagnosing and monitoring infectious and genetic diseases. The review aims to review the current status of AI-based NAT result visualization. It systematically introduces commonly used AI-based methods and techniques for NAT, emphasizing the importance of result visualization for accessible, clear, and rapid interpretation. This highlights the importance of developing a NAT visualization platform that is user-friendly and efficient, setting a clear direction for future advancements in making nucleic acid testing more accessible and effective for everyday applications.

Method

This review explores both the commonly used NAT methods and AI-based techniques for NAT result visualization. The focus then shifts to AI-based methodologies, such as color detection and result interpretation through AI algorithms. The article presents the advantages and disadvantages of these techniques, while also comparing the performance of various NAT platforms in different experimental contexts. Furthermore, it explores the role of AI in enhancing the accuracy, speed, and user accessibility of NAT results, highlighting visualization technologies adapted from other fields of experimentation.

Significance

This review offers valuable insights for researchers and everyday users, aiming to develop effective visualization platforms for NAT, ultimately enhancing disease diagnosis and monitoring.

Abstract Image

查看原文本刊更多论文

核酸检测的人工智能可视化。

目的：核酸检测（NAT）结果的可视化在诊断和监测传染病和遗传病方面发挥着至关重要的作用。本综述旨在回顾基于人工智能的 NAT 结果可视化的现状。它系统地介绍了常用的基于人工智能的 NAT 方法和技术，强调了结果可视化对于方便、清晰和快速解读的重要性。这凸显了开发用户友好、高效的 NAT 可视化平台的重要性，为未来使核酸检测在日常应用中更方便、更有效的进步指明了方向：本综述探讨了常用的 NAT 方法和基于人工智能的 NAT 结果可视化技术。然后重点转向基于人工智能的方法，如通过人工智能算法进行颜色检测和结果解读。文章介绍了这些技术的优缺点，同时还比较了各种 NAT 平台在不同实验环境下的性能。此外，文章还探讨了人工智能在提高 NAT 结果的准确性、速度和用户可访问性方面的作用，重点介绍了从其他实验领域借鉴的可视化技术：这篇综述为研究人员和日常用户提供了宝贵的见解，旨在为 NAT 开发有效的可视化平台，最终提高疾病诊断和监测水平。

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

Life sciences 医学-药学

CiteScore

12.20

自引率

1.60%

发文量

841

审稿时长

6 months

期刊介绍： Life Sciences is an international journal publishing articles that emphasize the molecular, cellular, and functional basis of therapy. The journal emphasizes the understanding of mechanism that is relevant to all aspects of human disease and translation to patients. All articles are rigorously reviewed. The Journal favors publication of full-length papers where modern scientific technologies are used to explain molecular, cellular and physiological mechanisms. Articles that merely report observations are rarely accepted. Recommendations from the Declaration of Helsinki or NIH guidelines for care and use of laboratory animals must be adhered to. Articles should be written at a level accessible to readers who are non-specialists in the topic of the article themselves, but who are interested in the research. The Journal welcomes reviews on topics of wide interest to investigators in the life sciences. We particularly encourage submission of brief, focused reviews containing high-quality artwork and require the use of mechanistic summary diagrams.