Lars Johannes Isaksson , Federico Mastroleo , Maria Giulia Vincini , Giulia Marvaso , Mattia Zaffaroni , Michał Gola , Giovanni Carlo Mazzola , Luca Bergamaschi , Simona Gaito , Filippo Alongi , Jerome Doyen , Piero Fossati , Karin Haustermans , Morten Høyer , Johannes Albertus Langendijk , Raùl Matute , Ester Orlandi , Marco Schwarz , Esther G.C. Troost , Vladimir Vondracek , Barbara Alicja Jereczek-Fossa
{"title":"人工智能在质子治疗中的新兴作用:综述。","authors":"Lars Johannes Isaksson , Federico Mastroleo , Maria Giulia Vincini , Giulia Marvaso , Mattia Zaffaroni , Michał Gola , Giovanni Carlo Mazzola , Luca Bergamaschi , Simona Gaito , Filippo Alongi , Jerome Doyen , Piero Fossati , Karin Haustermans , Morten Høyer , Johannes Albertus Langendijk , Raùl Matute , Ester Orlandi , Marco Schwarz , Esther G.C. Troost , Vladimir Vondracek , Barbara Alicja Jereczek-Fossa","doi":"10.1016/j.critrevonc.2024.104485","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to develop AI and machine learning tools to aid in various steps of the treatment planning and delivery processes. This review delves into the emergent role of AI in proton therapy, evaluating its development, advantages, intended clinical contexts, and areas of application. Through the analysis of 76 studies, we aim to underscore the importance of AI applications in advancing proton therapy and to highlight their prospective influence on clinical practices.</p></div>","PeriodicalId":11358,"journal":{"name":"Critical reviews in oncology/hematology","volume":"204 ","pages":"Article 104485"},"PeriodicalIF":5.5000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The emerging role of Artificial Intelligence in proton therapy: A review\",\"authors\":\"Lars Johannes Isaksson , Federico Mastroleo , Maria Giulia Vincini , Giulia Marvaso , Mattia Zaffaroni , Michał Gola , Giovanni Carlo Mazzola , Luca Bergamaschi , Simona Gaito , Filippo Alongi , Jerome Doyen , Piero Fossati , Karin Haustermans , Morten Høyer , Johannes Albertus Langendijk , Raùl Matute , Ester Orlandi , Marco Schwarz , Esther G.C. Troost , Vladimir Vondracek , Barbara Alicja Jereczek-Fossa\",\"doi\":\"10.1016/j.critrevonc.2024.104485\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to develop AI and machine learning tools to aid in various steps of the treatment planning and delivery processes. This review delves into the emergent role of AI in proton therapy, evaluating its development, advantages, intended clinical contexts, and areas of application. Through the analysis of 76 studies, we aim to underscore the importance of AI applications in advancing proton therapy and to highlight their prospective influence on clinical practices.</p></div>\",\"PeriodicalId\":11358,\"journal\":{\"name\":\"Critical reviews in oncology/hematology\",\"volume\":\"204 \",\"pages\":\"Article 104485\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Critical reviews in oncology/hematology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1040842824002282\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical reviews in oncology/hematology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1040842824002282","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEMATOLOGY","Score":null,"Total":0}
The emerging role of Artificial Intelligence in proton therapy: A review
Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to develop AI and machine learning tools to aid in various steps of the treatment planning and delivery processes. This review delves into the emergent role of AI in proton therapy, evaluating its development, advantages, intended clinical contexts, and areas of application. Through the analysis of 76 studies, we aim to underscore the importance of AI applications in advancing proton therapy and to highlight their prospective influence on clinical practices.
期刊介绍:
Critical Reviews in Oncology/Hematology publishes scholarly, critical reviews in all fields of oncology and hematology written by experts from around the world. Critical Reviews in Oncology/Hematology is the Official Journal of the European School of Oncology (ESO) and the International Society of Liquid Biopsy.