[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117908-en":3,"doc-seo-117908-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117908,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",7,"Healthcare","Early cancer detection by SERS spectroscopy and machine learning","A new approach for early detection of multiple cancers integrates SERS spectroscopy of serum molecular fingerprints with machine learning. Early detection of cancer or precancerous changes enables earlier intervention and can improve survival, while many cancers are still diagnosed at advanced stages. Existing screening methods include blood tests, histopathology, imaging, and genetic testing; however, challenges in validating biomarkers limit current blood-based options. The approach highlights SERS-AICS and emphasizes improved classification across multiple cancer types using efficient data analysis.","UC San Diego  \nUC San Diego Previously Published Works  \nTitle  \nEarly cancer detection by SERS spectroscopy and machine learning  \nPermalink  \n[https://escholarship.org/uc/item/2pr621xh](https://escholarship.org/uc/item/2pr621xh)  \nJournal  \nLight: Science & Applications, 12(1)  \nISSN  \n2095-5545  \nAuthors  \nShi, Lingyan  \nLi, Yajuan  \nLi, Zhi  \nPublication Date  \n2023  \nDOI  \n10.1038/s41377-023-01271-7  \nCopyright Information  \nThis work is made available under the terms of a Creative Commons Attribution License, available at [https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)  \nPeer reviewed  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nShi et al. Light: Science & Applications (2023)12:234 Official journal of the CIOMP 2047-7538  \n[https://doi.org/10.1038/s41377-023-01271-7](https://doi.org/10.1038/s41377-023-01271-7) [www.nature.com/lsa](www.nature.com/lsa)  \nNEWS & VIEWS Open Access  \nEarly cancer detection by SERS spectroscopy and machine learning  \nLingyan Shi1 ✉, Yajuan Li1 and Zhi Li1  \nAbstract  \nA new approach for early detection of multiple cancers is presented by integrating SERS spectroscopy of serum molecular fingerprints and machine learning.  \nCancer is a major public health problem and the second leading cause of death worldwide, with 10 million deaths in 20201. Early detection of cancer or precancerous change allows for early intervention and can improve survival rates. However, early detection of many cancers, such as esophageal and ovarian cancers, is still poor, which are often diagnosed at advanced stages2. This is more likely due to multiple remaining challenges, such as finding and validating biomarkers for multicancer types, and technologies applied for cancer detection2.  \nCurrent approaches for cancer screening and detection include blood tests, histopathology tests, imaging tests (for example, mammogram for breast cancer and computerized tomography for lung cancer), and genetic tests. Compared to histopathology and imaging tests, blood tests, which rely on the analysis of specific analytes and tumor biomarkers such as tumor DNA/protein and circulating tumor cells3, are noninvasive and more efficient. However, due to the challenge of validating many potential biomarkers for different cancer types, only a few biomarkers have been validated and used in clinic4.  \nSince the past decade, Raman and infrared spectroscopies have emerged for cancer diagnosis by detecting molecular vibrational fingerprints5. Studies utilized infrared spectroscopy and detected breast, bladder, prostate, and lung cancers via molecular fingerprints in blood plasma and serum6,7. Compared with infrared spectroscopy, various types of Raman spectroscopy are more  \nCorrespondence: Lingyan Shi ([l2shi@ucsd.edu](l2shi@ucsd.edu))  \n1Shu Chien-Gene Lay Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA  \ncommonly used for cancer detection. Among these, surface-enhanced Raman spectroscopy (SERS) measurement on blood samples is most frequently used in early cancer detection due to its high sensitivity and specificity8–12. Nevertheless, these studies were constrained by their utilization of a very limited set of biomarkers, rendering them unsuitable for detecting multiple types of cancer. Additionally, they lacked efficient data analysis methods. In contrast, the application of machine learning techniques has proven valuable in classifying serum biomarkers to detect cancer and other diseases using omics data13. However, machine learning requires a large independent dataset, while in the previous study only 10 out of a thousand dimensions could be selected for the machine learning algorithm13.  \nIn their article in Light14, Shilian Dong and colleagues presented a method for early cancer detection that uses label-free SERS spectroscopy and machine learning for cancer screening (SERS-AICS) of serum biomarkers. The workflow of SERS-A","cbCaibrpYXCnmLN1","https://ap.wps.com/l/cbCaibrpYXCnmLN1","pdf",439467,1,4,"English","en",105,"# Abstract\n## Background: cancer screening challenges\n## Current methods and limitations\n## Spectroscopy-based diagnosis\n## SERS-AICS and classification performance\n## Study design and data analysis","[{\"question\":\"What method does the document propose for early cancer detection?\",\"answer\":\"It proposes integrating SERS spectroscopy of serum molecular fingerprints with machine learning to classify multiple cancer types at early stages.\"},{\"question\":\"Why is early detection important according to the document?\",\"answer\":\"Early detection of cancer or precancerous changes allows earlier intervention, which can improve survival rates.\"},{\"question\":\"What limitations affect existing cancer detection and screening approaches?\",\"answer\":\"Many approaches rely on biomarkers that are difficult to validate across cancer types, and data analysis methods may be insufficient; thus only a few biomarkers are widely used clinically.\"}]","Early cancer detection by SERS spectroscopy and machine learning | PDF",1785680334,10,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":28},"early-cancer-detection-by-sers-spectroscopy-and-machine-learning","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":43,"position":21},"https://docshare.wps.com/document/early-cancer-detection-by-sers-spectroscopy-and-machine-learning/117908/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What method does the document propose for early cancer detection?","Question",{"text":74,"@type":75},"It proposes integrating SERS spectroscopy of serum molecular fingerprints with machine learning to classify multiple cancer types at early stages.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"Why is early detection important according to the document?",{"text":79,"@type":75},"Early detection of cancer or precancerous changes allows earlier intervention, which can improve survival rates.",{"name":81,"@type":72,"acceptedAnswer":82},"What limitations affect existing cancer detection and screening approaches?",{"text":83,"@type":75},"Many approaches rely on biomarkers that are difficult to validate across cancer types, and data analysis methods may be insufficient; 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