{"title":"磁共振神经成像中的可重复研究实践:以高级语言模型为基础的综述。","authors":"Agah Karakuzu, Mathieu Boudreau, Nikola Stikov","doi":"10.2463/mrms.rev.2023-0174","DOIUrl":null,"url":null,"abstract":"<p><p>MRI has progressed significantly with the introduction of advanced computational methods and novel imaging techniques, but their wider adoption hinges on their reproducibility. This concise review synthesizes reproducible research insights from recent MRI articles to examine the current state of reproducibility in neuroimaging, highlighting key trends and challenges. It also provides a custom generative pretrained transformer (GPT) model, designed specifically for aiding in an automated analysis and synthesis of information pertaining to the reproducibility insights associated with the articles at the core of this review.</p>","PeriodicalId":94126,"journal":{"name":"Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine","volume":" ","pages":"252-267"},"PeriodicalIF":3.2000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11234949/pdf/","citationCount":"0","resultStr":"{\"title\":\"Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.\",\"authors\":\"Agah Karakuzu, Mathieu Boudreau, Nikola Stikov\",\"doi\":\"10.2463/mrms.rev.2023-0174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>MRI has progressed significantly with the introduction of advanced computational methods and novel imaging techniques, but their wider adoption hinges on their reproducibility. This concise review synthesizes reproducible research insights from recent MRI articles to examine the current state of reproducibility in neuroimaging, highlighting key trends and challenges. It also provides a custom generative pretrained transformer (GPT) model, designed specifically for aiding in an automated analysis and synthesis of information pertaining to the reproducibility insights associated with the articles at the core of this review.</p>\",\"PeriodicalId\":94126,\"journal\":{\"name\":\"Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine\",\"volume\":\" \",\"pages\":\"252-267\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11234949/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2463/mrms.rev.2023-0174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2463/mrms.rev.2023-0174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.
MRI has progressed significantly with the introduction of advanced computational methods and novel imaging techniques, but their wider adoption hinges on their reproducibility. This concise review synthesizes reproducible research insights from recent MRI articles to examine the current state of reproducibility in neuroimaging, highlighting key trends and challenges. It also provides a custom generative pretrained transformer (GPT) model, designed specifically for aiding in an automated analysis and synthesis of information pertaining to the reproducibility insights associated with the articles at the core of this review.