Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer

被引:47
作者
Qiu, Hang [1 ,2 ]
Ding, Shuhan [3 ]
Liu, Jianbo [4 ,5 ]
Wang, Liya [1 ]
Wang, Xiaodong [4 ,5 ]
机构
[1] Univ Elect Sci & Technol China, Big Data Res Ctr, Chengdu 611731, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Peoples R China
[3] Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14853 USA
[4] Sichuan Univ, West China Sch Med, Chengdu 610041, Peoples R China
[5] Sichuan Univ, West China Hosp, Dept Gastrointestinal Surg, Chengdu 610041, Peoples R China
基金
中国国家自然科学基金;
关键词
colorectal cancer; artificial intelligence; machine learning; deep learning; diagnosis; prognosis; treatment; screening; RECTAL-CANCER; CT COLONOGRAPHY; PREDICTION; RISK; COLONOSCOPY; VALIDATION; RECURRENCE; SURVIVAL; SURGERY; LESIONS;
D O I
10.3390/curroncol29030146
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early detection and diagnosis, comprehensive assessment of treatment response, and precise prediction of prognosis are essential to improve the patients' survival rate. In recent years, due to the explosion of clinical and omics data, and groundbreaking research in machine learning, artificial intelligence (AI) has shown a great application potential in clinical field of CRC, providing new auxiliary approaches for clinicians to identify high-risk patients, select precise and personalized treatment plans, as well as to predict prognoses. This review comprehensively analyzes and summarizes the research progress and clinical application value of AI technologies in CRC screening, diagnosis, treatment, and prognosis, demonstrating the current status of the AI in the main clinical stages. The limitations, challenges, and future perspectives in the clinical implementation of AI are also discussed.
引用
收藏
页码:1773 / 1795
页数:23
相关论文
共 109 条
[1]   Artificial intelligence as the next step towards precision pathology [J].
Acs, B. ;
Rantalainen, M. ;
Hartman, J. .
JOURNAL OF INTERNAL MEDICINE, 2020, 288 (01) :62-81
[2]  
Akbari M, 2018, IEEE ENG MED BIO, P69, DOI 10.1109/EMBC.2018.8512197
[3]   Survivability prediction of colon cancer patients using neural networks [J].
Al-Bahrani, Reda ;
Agrawal, Ankit ;
Choudhary, Alok .
HEALTH INFORMATICS JOURNAL, 2019, 25 (03) :878-891
[4]   Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991-2020 [J].
Alizadehsani, Roohallah ;
Khosravi, Abbas ;
Roshanzamir, Mohamad ;
Abdar, Moloud ;
Sarrafzadegan, Nizal ;
Shafie, Davood ;
Khozeimeh, Fahime ;
Shoeibi, Afshin ;
Nahavandi, Saeid ;
Panahiazar, Maryam ;
Bishara, Andrew ;
Beygui, Ramin E. ;
Puri, Rishi ;
Kapadia, Samir ;
Tan, Ru-San ;
Acharya, U. Rajendra .
COMPUTERS IN BIOLOGY AND MEDICINE, 2021, 128
[5]  
[Anonymous], 2018, Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies
[6]   Global patterns and trends in colorectal cancer incidence and mortality [J].
Arnold, Melina ;
Sierra, Monica S. ;
Laversanne, Mathieu ;
Soerjomataram, Isabelle ;
Jemal, Ahmedin ;
Bray, Freddie .
GUT, 2017, 66 (04) :683-691
[7]   Radiogenomics in Colorectal Cancer [J].
Badic, Bogdan ;
Tixier, Florent ;
Cheze Le Rest, Catherine ;
Hatt, Mathieu ;
Visvikis, Dimitris .
CANCERS, 2021, 13 (05) :1-22
[8]   Artificial Intelligence (AI)-Based Systems Biology Approaches in Multi-Omics Data Analysis of Cancer [J].
Biswas, Nupur ;
Chakrabarti, Saikat .
FRONTIERS IN ONCOLOGY, 2020, 10
[9]   Suboptimal surgery and omission of neoadjuvant therapy for upper rectal cancer is associated with a high risk of local recurrence [J].
Bondeven, P. ;
Laurberg, S. ;
Hagemann-Madsen, R. H. ;
Pedersen, B. Ginnerup .
COLORECTAL DISEASE, 2015, 17 (03) :216-224
[10]   Deep learning based tissue analysis predicts outcome in colorectal cancer [J].
Bychkov, Dmitrii ;
Linder, Nina ;
Turkki, Riku ;
Nordling, Stig ;
Kovanen, Panu E. ;
Verrill, Clare ;
Walliander, Margarita ;
Lundin, Mikael ;
Haglund, Caj ;
Lundin, Johan .
SCIENTIFIC REPORTS, 2018, 8