{"title":"核酸检测的人工智能可视化。","authors":"Zehua Lu, Xiaogang Wang, Junge Chen","doi":"10.1016/j.lfs.2024.123209","DOIUrl":null,"url":null,"abstract":"<div><h3>Aims</h3><div>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.</div></div><div><h3>Method</h3><div>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.</div></div><div><h3>Significance</h3><div>This review offers valuable insights for researchers and everyday users, aiming to develop effective visualization platforms for NAT, ultimately enhancing disease diagnosis and monitoring.</div></div>","PeriodicalId":18122,"journal":{"name":"Life sciences","volume":"359 ","pages":"Article 123209"},"PeriodicalIF":5.2000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI-empowered visualization of nucleic acid testing\",\"authors\":\"Zehua Lu, Xiaogang Wang, Junge Chen\",\"doi\":\"10.1016/j.lfs.2024.123209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Aims</h3><div>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.</div></div><div><h3>Method</h3><div>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.</div></div><div><h3>Significance</h3><div>This review offers valuable insights for researchers and everyday users, aiming to develop effective visualization platforms for NAT, ultimately enhancing disease diagnosis and monitoring.</div></div>\",\"PeriodicalId\":18122,\"journal\":{\"name\":\"Life sciences\",\"volume\":\"359 \",\"pages\":\"Article 123209\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Life sciences\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0024320524007999\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Life sciences","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0024320524007999","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
AI-empowered visualization of nucleic acid testing
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.
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.