人工智能在卵巢癌诊断与治疗中的应用进展： 从影像识别到精准医学

The Application Progress of Artificial Intelligence in the Diagnosis and Treatment of Ovarian Cancer: From Image Recognition to Precision Medicine

摘要: 卵巢癌作为女性生殖系统中致死率较高的恶性肿瘤之一，其早期诊断和精准治疗一直是临床研究的重点难题。近年来，人工智能技术的迅猛发展为卵巢癌的诊断与治疗带来了新的机遇。本文综述了人工智能技术在卵巢癌领域的最新应用进展，尤其聚焦基于机器学习和深度学习的影像识别、病理分析、基因组学研究及生物标志物发现等方面。通过整合多模态数据，人工智能技术显著提升了卵巢癌早期检测的准确性和病理分类的精细度，为预后评估和药物耐药性分析提供了有力支持，推动了个性化精准医疗的发展。然而，数据质量良莠不齐、模型的可解释性不足及临床应用的转化难题仍限制了人工智能技术的广泛应用。未来，随着多学科融合和技术优化，人工智能技术有望在卵巢癌诊疗中发挥更大作用，实现更精准、高效的临床决策支持。

Abstract: Ovarian cancer, as one of the malignant tumors with a relatively high mortality rate in the female reproductive system, its early diagnosis and precise treatment have always been key challenges in clinical research. In recent years, the rapid development of artificial intelligence technology has brought new opportunities for the diagnosis and treatment of ovarian cancer. This article reviews the latest application progress of artificial intelligence technology in the field of ovarian cancer, with a particular focus on aspects such as image recognition, pathological analysis, genomic research, and biomarker discovery based on machine learning and deep learning. By integrating multimodal data, artificial intelligence technology has significantly enhanced the accuracy of early detection of ovarian cancer and the fineness of pathological classification, providing strong support for prognosis assessment and drug resistance analysis, and promoting the development of personalized precision medicine. However, the uneven quality of data, the insufficient interpretability of models, and the challenges in transforming them into clinical applications still limit the wide application of artificial intelligence technology. In the future, with the integration of multiple disciplines and technological optimization, artificial intelligence technology is expected to play a greater role in the diagnosis and treatment of ovarian cancer, achieving more precise and efficient clinical decision support.