[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-290744-105":59,"doc-detail-290744-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","simple-machine-learning-methods-work-surprisingly-well-for-ramanomics-short-communication","Simple machine learning methods work surprisingly well for Ramanomics - Short communication","","Recently, a deep convolutional neural network was used in Ramanomics to detect liver cancer, with demo results claiming roughly 90% accuracy after about an hour of training on a desktop. This work tests simpler, interpretable alternatives instead. Logistic regression reaches about 90.4% accuracy in under a minute, while a random decision forest attains about 92.6% accuracy in under 10 seconds. The findings suggest deep learning remains promising but may not deliver a quantum leap; more Ramanomics-aware machine learning approaches are desired.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/simple-machine-learning-methods-work-surprisingly-well-for-ramanomics-short-communication/290744/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/simple-machine-learning-methods-work-surprisingly-well-for-ramanomics-short-communication/290744.png","ImageObject",300,407,{"name":92,"@type":93},"Miles","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-18","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",14,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What deep learning approach is discussed in the document?","Question",{"text":113,"@type":114},"A deep convolutional neural network was used for Ramanomics-based liver cancer detection, with reported demo performance around 90% accuracy after about an hour of training.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which simpler machine learning methods are tested, and what accuracy do they achieve?",{"text":118,"@type":114},"The paper tests logistic regression and a random decision forest. Logistic regression achieves about 90.4% accuracy in under a minute, and the random decision forest achieves about 92.6% accuracy in under 10 seconds.",{"name":120,"@type":111,"acceptedAnswer":121},"What conclusion does the document draw about deep learning for Ramanomics?",{"text":122,"@type":114},"Deep learning is considered promising, but the results indicate it does not provide a major performance leap for Ramanomics in this context, motivating more Ramanomics-aware machine learning methods.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},290744,1789642488,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":24,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":144,"preview_page_count":4},13056703019404,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","University of Groningen  \nSimple machine learning methods work surprisingly well for Ramanomics  \nLawrence, Celestine P.  \nPublished in:  \nJournal of Raman Spectroscopy  \nDOI:  \n10.1002/jrs.6555  \nIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nPublication date: 2023  \nLink to publication in University of Groningen/UMCG research database  \nCitation for published version (APA):  \nLawrence, C. P. (2023) . Simple machine learning methods work surprisingly well for Ramanomics. Journal of Raman Spectroscopy, 54(8), 887-889 . [https://doi.org/10.1002/jrs.6555](https://doi.org/10.1002/jrs.6555)  \nCopyright  \nOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons) .  \nThe publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: [https://www.rug.nl/library/open-access/self-archiving-pure/taverne](https://www.rug.nl/library/open-access/self-archiving-pure/taverne)amendment.  \nTake-down policy  \nIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.  \nDownloaded from the University of Groningen/U MCG research database (Pure): [http://www.rug. nl/research/portal. For technical reasons the](http://www.rug. nl/research/portal. For technical reasons the)[ ](http://www.rug. nl/research/portal. For technical reasons the)[number of authors shown on this cover page is limited to 10 maximum.](number of authors shown on this cover page is limited to 10 maximum.)  \nDownload date: 29-12-2025  \nReceived: 15 February 2023 Revised: 4 May 2023 Accepted: 5 May 2023  \nDOI: 10.1002/jrs.6555  \nSHO RT C OMM UNICA TI ON  \nSimple machine learning methods work surprisingly well for Ramanomics  \nCelestine P. Lawrence   \nBernoulli Institute and Groningen Cognitive Systems and Materials Center (CogniGron), University of Groningen, Groningen, Netherlands  \nCorrespondence  \nCelestine P. Lawrence, Bernoulli Institute and Groningen Cognitive Systems and Materials Center (CogniGron), University of Groningen, 9700 AB, Groningen, Netherlands.  \nEmail: [c.p.lawrence@rug.nl](c.p.lawrence@rug.nl)  \nAbstract  \nRecently, a deep convolutional neural network was employed to detect liver cancer by Ramanomics. Results on a demo dataset claimed an accuracy of about 90% to be achieved after around an hour of training in a modern desktop. However, my experience with another Ramanomics dataset taught me that simple methods could potentially outperform deep learning. Here, I tested the simple and interpretable method of logistic regression. It achieved an accuracy of around 90.4% in under a minute. Employing a random decision forest yieldsan accuracy of 92.6% in under 10 s. Thus, although deep learning is promising, it is yet to provide a quantum-leap in performance for Ramanomics. A biophysics aware machine learning method would be more welcome!  \nKEYWOR DS  \nmachine learning, Raman spectroscopy  \n1 | INTRODUCTION  \nClassification of Raman spectra by deep learning methods has been a topic of interest for over three decades.1 With the recent success of deep learning, in scientific domains such as protein folding,2 there also seems to be a growing wave of interest in deep learning for Ramanomics.3,4 However, simpler machine learning methods could potentially outperform deep learning methods.5 I personally found this to be true, on a dataset in the wild, when I could gain a 0.5% in accuracy for the classification of pathogenic bacteria by their Raman spectr","cbCaiujVVmSBkIyh","https://ap.wps.com/l/cbCaiujVVmSBkIyh","pdf",840796,"English","# Abstract\n# 1 | Introduction\n# 2 | Results","[{\"question\":\"What deep learning approach is discussed in the document?\",\"answer\":\"A deep convolutional neural network was used for Ramanomics-based liver cancer detection, with reported demo performance around 90% accuracy after about an hour of training.\"},{\"question\":\"Which simpler machine learning methods are tested, and what accuracy do they achieve?\",\"answer\":\"The paper tests logistic regression and a random decision forest. Logistic regression achieves about 90.4% accuracy in under a minute, and the random decision forest achieves about 92.6% accuracy in under 10 seconds.\"},{\"question\":\"What conclusion does the document draw about deep learning for Ramanomics?\",\"answer\":\"Deep learning is considered promising, but the results indicate it does not provide a major performance leap for Ramanomics in this context, motivating more Ramanomics-aware machine learning methods.\"}]","Simple machine learning methods work surprisingly well for Ramanomics - Short communication | PDF",13]