Citations

Citations to this article as recorded by  

• Explainable AI for colorectal cancer mortality and risk factor prediction in Korea: A nationwide cancer cohort study
  Sang Won Park, Na Young Yeo, Tae-Hoon Kim, Myoung Nam Lim, Inhyeok Yim, Oh Beom Kwon, Seung-Joo Nam, Hui-Young Lee, Woo Jin Kim
  International Journal of Medical Informatics.2026; 205: 106125.     CrossRef
• A clinical visualization model for predicting distant metastasis and prognostic outcomes in mucinous adenocarcinoma of the appendix: a SEER database study
  Xiaoming Xu, Hualei Chen, Jingzhi Wang
  Expert Review of Anticancer Therapy.2026; 26(1): 131.     CrossRef
• Predicting Postresection Colorectal Liver Metastases Recurrence Using Advanced Graph Neural Networks with Explainability and Causal Inference
  Jubair Ahmed, Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Sami Azam
  Advanced Intelligent Systems.2026;[Epub]     CrossRef
• Artificial Intelligence Remote Patient Monitoring for Predicting Overall Survival for Patients Undergoing Radical Cystectomy for Bladder Cancer: Exploratory Analysis of the Prospective Trial
  Yansong Liu, Pramit Khetrapal, Ronnie Strafford, Adamos Hadjivasilou, Nikhil Vasdev, Philip Charlesworth, Muhamaad Shamim Khan, Ahmed Abdulaal, Zhaoyan Dong, James W F Catto, Yukun Zhou, John D Kelly, Ivana Drobnjak
  JMIR AI.2026; 5: e68994.     CrossRef
• A Hybrid Deep and Machine Learning Framework with Feature Selection for Automated Classification of Acute Lymphoblastic Leukemia
  Husne Farah, Fahmida Islam, Shuvo Biswas, Mohammad Shorif Uddin
  Journal of Computer and Communications.2026; 14(03): 278.     CrossRef
• AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review
  Bhagvat J Maheta, Rachel L Ross, Isabella Raspi, Christina Keny, Marti N Okech, Selen Bozkurt, Karleen F Giannitrapani
  JMIR Perioperative Medicine.2026; 9: e89936.     CrossRef
• Development and validation of a biomarker-based prediction model for metastasis in patients with colorectal cancer: Application of machine learning algorithms
  Erfan Ayubi, Sajjad Farashi, Leili Tapak, Saeid Afshar
  Heliyon.2025; 11(1): e41443.     CrossRef
• Predicting Factors Affecting Survival Rate in Patients Undergoing On‐Pump Coronary Artery Bypass Graft Surgery Using Machine Learning Methods: A Systematic Review
  Alireza Jafarkhani, Behzad Imani, Soheila Saeedi, Amir Shams
  Health Science Reports.2025;[Epub]     CrossRef
• Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review
  Catarina Sousa Santos, Mário Amorim-Lopes
  BMC Medical Research Methodology.2025;[Epub]     CrossRef
• Personalized surveillance in colorectal cancer: Integrating circulating tumor DNA and artificial intelligence into post-treatment follow-up
  Ionut Negoi
  World Journal of Gastroenterology.2025;[Epub]     CrossRef
• Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model
  Feng Cui, Xiangji Dang, Daiyun Peng, Yuanhua She, Yubin Wang, Ruifeng Yang, Zhiyao Han, Yan Liu, Hanteng Yang
  BMC Cancer.2025;[Epub]     CrossRef
• Interpretable machine learning models based on body composition and inflammatory nutritional index (BCINI) to predict early postoperative recurrence of colorectal cancer: Multi-center study
  Yongjie Zhou, Jinhong Zhao, Fei Zou, Yongming Tan, Wei Zeng, Jiahui Jiang, Jiale Hu, Qiao Zeng, Lianggeng Gong, Lan Liu, Linhua Zhong
  Computer Methods and Programs in Biomedicine.2025; 269: 108874.     CrossRef
• Leveraging automated machine learning to predict colon cancer prognosis from clinical features and risk groups: a retrospective cohort study
  Jakob Woerner, Yonghyun Nam, Sang-Hyuk Jung, Manu Shivakumar, Matthew Lee, Eun Kyung Choe, Min Jung Kim, Rumi Shin, Seung-Bum Ryoo, Seung-Yong Jeong, Kyu Joo Park, Sung Chan Park, Dae Kyung Sohn, Jae Hwan Oh, Dokyoon Kim, Ji Won Park
  European Journal of Surgical Oncology.2025; 51(9): 110194.     CrossRef
• Integrating inflammation, nutrition, and artificial intelligence: A new era in colorectal cancer prognostic scoring
  Semra Demirli Atici, Aras Emre Canda, Mustafa Cem Terzi
  World Journal of Gastroenterology.2025;[Epub]     CrossRef
• Artificial intelligence for predicting long-term outcomes in patients with colorectal cancer (a systematic review and meta-analysis)
  R. Sh. Abdulaeva, V. I. Pavlova, T. G. Gevorkyan, Y. V. Belenkaya, M. Sh. Manukyan, S. S. Gordeev
  Koloproktologia.2025; 24(4): 125.     CrossRef
• New perspectives on cancer clinical research in the era of big data and machine learning
  Shujun Li, Hang Yi, Qihao Leng, You Wu, Yousheng Mao
  Surgical Oncology.2024; 52: 102009.     CrossRef
• SAGL: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients
  Ping Yang, Hang Qiu, Xulin Yang, Liya Wang, Xiaodong Wang
  Computer Methods and Programs in Biomedicine.2024; 249: 108159.     CrossRef
• The development and validation of automated machine learning models for predicting lymph node metastasis in Siewert type II T1 adenocarcinoma of the esophagogastric junction
  Chenghao Lu, Lu Liu, Minyue Yin, Jiaxi Lin, Shiqi Zhu, Jingwen Gao, Shuting Qu, Guoting Xu, Lihe Liu, Jinzhou Zhu, Chunfang Xu
  Frontiers in Medicine.2024;[Epub]     CrossRef
• Machine learning for predicting colon cancer recurrence
  Erkan Kayikcioglu, Arif Hakan Onder, Burcu Bacak, Tekin Ahmet Serel
  Surgical Oncology.2024; 54: 102079.     CrossRef
• Precision prognosis of colorectal cancer: a multi-tiered model integrating microsatellite instability genes and clinical parameters
  Yonghong Wang, Ke Liu, Wanbin He, Jie Dan, Mingjie Zhu, Lei Chen, Wenjie Zhou, Ming Li, Jiangpeng Li
  Frontiers in Oncology.2024;[Epub]     CrossRef
• Light gradient boost tree classifier predictions on appendicitis with periodontal disease from biochemical and clinical parameters
  Pradeep Kumar Yadalam, Prathiksha Vedhavalli Thirukkumaran, Prabhu Manickam Natarajan, Carlos M. Ardila
  Frontiers in Oral Health.2024;[Epub]     CrossRef
• Enhanced prediction of preoperative mesenteric lymph node metastasis in colorectal cancer using machine learning with CT‐based data
  Lanni Zhou, Lizhu Ouyang, Baoliang Guo, Xiyi Huang, Shaomin Yang, Jialing Pan, Liwen Wang, Ming Chen, Fan Xie, Yunjing Li, Yongxing Du, Xinjie Chen, Qiugen Hu, Fusheng Ouyang
  MedComm – Future Medicine.2024;[Epub]     CrossRef
• An interactive web-based tool for predicting and exploring brain cancer survivability
  Gopal Nath, Austin Coursey, Yang Li, Srikanth Prabhu, Harish Garg, Shaymal C. Halder, Saptarshi Sengupta
  Healthcare Analytics.2023; 3: 100132.     CrossRef
• Statistical and machine learning approaches to predict the necessity for computed tomography in children with mild traumatic brain injury
  Tadashi Miyagawa, Marina Saga, Minami Sasaki, Miyuki Shimizu, Akira Yamaura, Alvan Ukachukwu
  PLOS ONE.2023; 18(1): e0278562.     CrossRef
• Machine learning for prediction of in-hospital mortality in lung cancer patients admitted to intensive care unit
  Tianzhi Huang, Dejin Le, Lili Yuan, Shoujia Xu, Xiulan Peng, Samuele Ceruti
  PLOS ONE.2023; 18(1): e0280606.     CrossRef
• Application of Artificial Intelligence in Gastrointestinal Cancer
  洪铭 崔
  Advances in Clinical Medicine.2023; 13(03): 3942.     CrossRef
• Clinicopathologic and prognostic factors of patients with T3/T4 colorectal signet ring cell carcinoma: a population-based study
  Fan Zhang, Boqi Xu, Yao Peng, Zhongqi Mao
  Journal of Cancer Research and Clinical Oncology.2023; 149(12): 9747.     CrossRef
• Using machine learning algorithms to predict 28-day mortality in critically ill elderly patients with colorectal cancer
  Chunxia Guo, Jun Pan, Shan Tian, Yuanjun Gao
  Journal of International Medical Research.2023;[Epub]     CrossRef