{"title":"基于人工智能的方法:实现肺癌筛查和评估公平性的前进道路","authors":"Stephen J. Kuperberg, David C. Christiani","doi":"10.1002/cai2.70019","DOIUrl":null,"url":null,"abstract":"<p>Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70019","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence-Based Methods: The Path Forward in Achieving Equity in Lung Cancer Screening and Evaluation\",\"authors\":\"Stephen J. Kuperberg, David C. Christiani\",\"doi\":\"10.1002/cai2.70019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.\\n <figure>\\n <div><picture>\\n <source></source></picture><p></p>\\n </div>\\n </figure></p>\",\"PeriodicalId\":100212,\"journal\":{\"name\":\"Cancer Innovation\",\"volume\":\"4 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70019\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cai2.70019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Innovation","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cai2.70019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Intelligence-Based Methods: The Path Forward in Achieving Equity in Lung Cancer Screening and Evaluation
Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.