Artificial intelligence in oncological imaging screening
Year: 2025
Type: article
Abstract: The global cancer burden continues to escalate, driven by a significant rise in new cases and cancer-related deaths. Early detection through effective screening programs is paramount for reducing mortality, and the integration of Artificial Intelligence (AI) into oncological imaging has shown transformative potential. This review comprehensively examines the evolution and clinical application of AI in oncological imaging for cancer detection across various modalities, including ultrasound, X-ray, computed tomography, magnetic resonance imaging, and endoscopy, highlighting significant advancements in early cancer screening. We further address the challenges associated with AI implementation in medical imaging, including dataset bias, the need for robust regulatory frameworks, and technical integration barriers. Emphasis is placed on the necessity of standardized, diverse datasets, explainable algorithms, and equitable implementation to mitigate disparities. By aligning technological innovation with rigorous clinical validation, ethical governance, and seamless workflow integration, AI is poised to revolutionize cancer care through earlier and more accurate detection, personalized risk stratification, and ultimately, improved patient outcomes.
Source: International Journal of Surgery
Authors: Zhihong Guo, Meng Xu, Chaoliang Zhong, Xiaoyi Yin, Beilei Wang, Gang Jin
Institutions: Second Military Medical University, Changhai Hospital
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,450
OpenAlex ID: W4416616978