Second Department of Surgery, University General Hospital of Alexandroupolis, Democritus University of Thrace Medical School, Dragana, 68100 Alexandroupolis, Greece.
Laboratory of Experimental Surgery & Surgical Research, Democritus University of Thrace Medical School, Dragana, 68100 Alexandroupolis, Greece.
Curr Oncol. 2021 Apr 23;28(3):1581-1607. doi: 10.3390/curroncol28030149.
The development of artificial intelligence (AI) algorithms has permeated the medical field with great success. The widespread use of AI technology in diagnosing and treating several types of cancer, especially colorectal cancer (CRC), is now attracting substantial attention. CRC, which represents the third most commonly diagnosed malignancy in both men and women, is considered a leading cause of cancer-related deaths globally. Our review herein aims to provide in-depth knowledge and analysis of the AI applications in CRC screening, diagnosis, and treatment based on current literature. We also explore the role of recent advances in AI systems regarding medical diagnosis and therapy, with several promising results. CRC is a highly preventable disease, and AI-assisted techniques in routine screening represent a pivotal step in declining incidence rates of this malignancy. So far, computer-aided detection and characterization systems have been developed to increase the detection rate of adenomas. Furthermore, CRC treatment enters a new era with robotic surgery and novel computer-assisted drug delivery techniques. At the same time, healthcare is rapidly moving toward precision or personalized medicine. Machine learning models have the potential to contribute to individual-based cancer care and transform the future of medicine.
人工智能 (AI) 算法的发展在医学领域取得了巨大成功。人工智能技术在诊断和治疗多种癌症，特别是结直肠癌 (CRC) 中的广泛应用，现在引起了广泛关注。CRC 在男性和女性中是第三大常见恶性肿瘤，被认为是全球癌症相关死亡的主要原因。我们的综述旨在根据现有文献深入了解和分析人工智能在 CRC 筛查、诊断和治疗中的应用。我们还探讨了人工智能系统在医学诊断和治疗方面的最新进展的作用，取得了一些有前途的结果。CRC 是一种高度可预防的疾病，常规筛查中的人工智能辅助技术代表着降低这种恶性肿瘤发病率的关键一步。到目前为止，已经开发出计算机辅助检测和特征描述系统来提高腺瘤的检测率。此外，CRC 治疗进入了机器人手术和新型计算机辅助药物输送技术的新时代。与此同时，医疗保健正在迅速向精准或个性化医疗发展。机器学习模型有可能为基于个体的癌症护理做出贡献，并改变医学的未来。
