Applications of Artificial Intelligence for Metastatic Gastrointestinal Cancer: A Systematic Literature Review.

IF 4.4 2区医学 Q1 ONCOLOGY Cancers Pub Date : 2025-02-06 DOI:10.3390/cancers17030558

Amin Naemi, Ashkan Tashk, Amir Sorayaie Azar, Tahereh Samimi, Ghanbar Tavassoli, Anita Bagherzadeh Mohasefi, Elaheh Nasiri Khanshan, Mehrdad Heshmat Najafabad, Vafa Tarighi, Uffe Kock Wiil, Jamshid Bagherzadeh Mohasefi, Habibollah Pirnejad, Zahra Niazkhani

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Abstract

Background/objectives: This systematic literature review examines the application of Artificial Intelligence (AI) in the diagnosis, treatment, and follow-up of metastatic gastrointestinal cancers.

Methods: The databases PubMed, Scopus, Embase (Ovid), and Google Scholar were searched for published articles in English from January 2010 to January 2022, focusing on AI models in metastatic gastrointestinal cancers.

Results: forty-six studies were included in the final set of reviewed papers. The critical appraisal and data extraction followed the checklist for systematic reviews of prediction modeling studies. The risk of bias in the included papers was assessed using the prediction risk of bias assessment tool.

Conclusions: AI techniques, including machine learning and deep learning models, have shown promise in improving diagnostic accuracy, predicting treatment outcomes, and identifying prognostic biomarkers. Despite these advancements, challenges persist, such as reliance on retrospective data, variability in imaging protocols, small sample sizes, and data preprocessing and model interpretability issues. These challenges limit the generalizability, clinical application, and integration of AI models.

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人工智能在转移性胃肠癌中的应用：系统文献综述。

背景/目的：本系统文献综述探讨了人工智能（AI）在转移性胃肠道癌症的诊断、治疗和随访中的应用。方法：检索PubMed、Scopus、Embase （Ovid）和谷歌Scholar数据库2010年1月至2022年1月发表的英文论文，重点研究AI模型在转移性胃肠癌中的应用。结果：46项研究被纳入最终的综述论文。关键评估和数据提取遵循预测建模研究的系统审查清单。使用预测偏倚风险评估工具对纳入论文的偏倚风险进行评估。结论：人工智能技术，包括机器学习和深度学习模型，在提高诊断准确性、预测治疗结果和识别预后生物标志物方面显示出了希望。尽管取得了这些进步，但仍然存在挑战，例如对回顾性数据的依赖、成像方案的可变性、小样本量、数据预处理和模型可解释性问题。这些挑战限制了人工智能模型的推广、临床应用和集成。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancers Medicine-Oncology

CiteScore

8.00

自引率

9.60%

发文量

5371

审稿时长

18.07 days

期刊介绍： Cancers (ISSN 2072-6694) is an international, peer-reviewed open access journal on oncology. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.