Application and Prospects of Artificial Intelligence in the Diagnosis and Treatment of Endometrial Cancer

doi:10.12280/gjfckx.20240489

Abstract

Abstract:

The increasing incidence of endometrial cancer has driven innovations in diagnostic and therapeutic approaches. Among these, artificial intelligence (AI) technologies, particularly advances in deep learning and machine learning, have opened up new possibilities for improving diagnostic accuracy and developing personalized treatment plans. AI significantly enhances early detection and diagnostic precision for endometrial cancer through improved medical image analysis, automated pathological image interpretation, and in-depth genomic data analysis. Additionally, AI aids in personalized treatment decisions and prognosis evaluation by integrating multi-source data to accurately predict treatment outcomes. Recent research has focused on data fusion and real-time patient monitoring applications, further exploring AI′s potential in the comprehensive management of endometrial cancer patients. However, the widespread application of AI still faces challenges related to data quality, generalization, interpretability, and associated legal and ethical issues. Therefore, realizing the full potential of AI in the entire management process of endometrial cancer requires continuous technological innovation and interdisciplinary collaboration to ensure the reasonable, transparent, and safe application of these technologies. This presents a positive outlook for the future of healthcare, aiming to optimize treatment outcomes and improve patients′ quality of life through technological advancements.

Key words: Endometrial neoplasms, Artificial intelligence, Machine learning, Prognosis, Diagnosis

HE Qing, HU Hong-bo. Application and Prospects of Artificial Intelligence in the Diagnosis and Treatment of Endometrial Cancer[J]. Journal of International Obstetrics and Gynecology, 2024, 51(5): 572-577.

Figures/Tables 1

References 39

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