Integrating artificial intelligence into radiological cancer imaging:from diagnosis and treatment response to prognosis  

作　　者：Sunyi Zheng Xiaonan Cui Zhaoxiang Ye 

机构地区：[1]Tianjin Medical University Cancer Institute and Hospital,National Clinical Research Center for Cancer,Tianjin’s Clinical Research Center for Cancer,State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine,Tianjin Key Laboratory of Digestive Cancer,Key Laboratory of Cancer Prevention and Therapy,Department of Radiology,Tianjin 300060,China

出　　处：《Cancer Biology & Medicine》2025年第1期6-13,共8页癌症生物学与医学(英文版)

基　　金：funded by grants from the National Natural Science Foundation of China(Grant Nos.82171932 and 82302180);the Ministry of Science and Technology of China(Grant No.2024ZD0520002);the Chinese National Key Research and Development Project(Grant Nos.2021YFC2500402 and 2021YFC2500400);the National Health Commission Capacity Building and Continuing Education Center(Grant No.YXFSC2022JJSJ011);the Tianjin Key Medical Discipline(Specialty)Construction Project(Grant No.TJYXZDXK-010A);the Scientific Developing Foundation of Tianjin Education Commission(Grant No.2024KJ182).

摘　　要：Cancer poses a serious threat to human health worldwide and is a leading cause of death1.The analysis of radiological imaging is crucial in early detection,accurate diagnosis,effective treatment planning,and ongoing monitoring of patients with cancer.However,several challenges impede the effectiveness of cancer imaging analysis in clinical practice.One difficulty is that healthcare professionals’immense clinical workloads can result in time constraints and increase pressure,thereby hindering their ability to maintain high accuracy and thoroughness in image analysis.Additionally,subjective variability among radiologists can lead to inconsistent interpretations and diagnoses.Because this variability is often influenced by personal biases,standardized assessments are often difficult to achieve.Moreover,the inherent complexity of cancer imaging necessitates extensive clinical experience;this aspect can also be a limiting factor,particularly if expertise or resources are limited.The application of artificial intelligence(AI)can alleviate these problems by enhancing the accuracy,objectivity,and efficiency of cancer imaging analysis while assisting physicians.Therefore,the advancement of AI research is crucial for achieving progress in radiology.

关 键 词：DIAGNOSIS artificial TREATMENT 

分 类 号：R730.44[医药卫生—肿瘤] TP18[医药卫生—临床医学] TP391.41[自动化与计算机技术—控制理论与控制工程]