Garg Pankaj, Mohanty Atish, Ramisetty Sravani, Kulkarni Prakash, Horne David, Pisick Evan, Salgia Ravi, Singhal Sharad S
Department of Chemistry, GLA University, Mathura, Uttar Pradesh 281406, India.
Departments of Medical Oncology & Therapeutics Research, Molecular Medicine, Beckman Research Institute of City of Hope, Comprehensive Cancer Center and National Medical Center, Duarte, CA 91010, USA.
Biochim Biophys Acta Rev Cancer. 2023 Nov;1878(6):189026. doi: 10.1016/j.bbcan.2023.189026. Epub 2023 Nov 20.
Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the greatest threat to world health, with early identification being crucial to patient outcomes and survival rates. The application of machine learning (ML) and artificial intelligence (AI) approaches to the study of gynecological cancer has shown potential to revolutionize cancer detection and diagnosis. The current review outlines the significant advancements, obstacles, and prospects brought about by AI and ML technologies in the timely identification and accurate diagnosis of different types of gynecological cancers. The AI-powered technologies can use genomic data to discover genetic alterations and biomarkers linked to a particular form of gynecologic cancer, assisting in the creation of targeted treatments. Furthermore, it has been shown that the potential benefits of AI and ML technologies in gynecologic tumors can greatly increase the accuracy and efficacy of cancer diagnosis, reduce diagnostic delays, and possibly eliminate the need for needless invasive operations. In conclusion, the review focused on the integrative part of AI and ML based tools and techniques in the early detection and exclusion of various cancer types; together with a collaborative coordination between research clinicians, data scientists, and regulatory authorities, which is suggested to realize the full potential of AI and ML in gynecologic cancer care.
妇科癌症包括乳腺癌、宫颈癌、卵巢癌、子宫癌和阴道癌，对全球健康构成最大威胁，早期识别对患者的治疗结果和生存率至关重要。将机器学习（ML）和人工智能（AI）方法应用于妇科癌症研究已显示出变革癌症检测和诊断的潜力。本综述概述了人工智能和机器学习技术在及时识别和准确诊断不同类型妇科癌症方面所取得的重大进展、面临的障碍和前景。人工智能驱动的技术可以利用基因组数据发现与特定形式妇科癌症相关的基因改变和生物标志物，有助于开发靶向治疗方法。此外，研究表明，人工智能和机器学习技术在妇科肿瘤中的潜在益处可以大大提高癌症诊断的准确性和有效性，减少诊断延迟，并可能消除不必要的侵入性手术需求。总之，本综述重点关注基于人工智能和机器学习的工具和技术在早期检测和排除各种癌症类型方面的整合部分；同时建议研究临床医生、数据科学家和监管机构之间进行协作协调，以充分发挥人工智能和机器学习在妇科癌症护理中的潜力。
