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Advanced AI-based technologies for early detection and personalized management of cervical cancer

Year: 2025

Type: article

Abstract: Cervical cancer is one of the leading causes of cancer-related deaths among women worldwide, imposing a particularly heavy burden in low- and middle-income countries. In recent years, advanced artificial intelligence (AI)-based technologies, including convolutional neural networks (CNNs) for image analysis and natural language processing (NLP) of electronic health records (EHRs), have substantially improved detection performance, individualized risk prediction, and the design of tailored treatment regimens. By leveraging expert visual recognition and synthesizing multimodal clinical data, these approaches offer the potential for more accurate screening and faster diagnosis. However, routine adoption hinges on resolving issues of data heterogeneity, algorithm interpretability, and ethical deployment. In this review, we summarize the latest AI breakthroughs in cervical cancer management, emphasize their promise for enhancing early intervention and personalized therapy, and call for rigorous validation to ensure safe, equitable integration into practice.

Source: Biomedical Technology

DOI: 10.1016/j.bmt.2025.100100

Authors: Yuheng Zhang, Yazhang Xu, Chenxin Wang, Zengjie Zhang, Kailiang Zhou, Yueliang Zhu, Xiaohua Yu

Institutions: Wenzhou Medical University, Second Affiliated Hospital of Zhejiang University, Zhejiang University, Harvard University, Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4413882287

FWCI: 3.263

Cites: 91

Cited by: 8

Related to: 10