ARTIFICIAL INTELLIGENCE IN EARLY CANCER DETECTION: A NEW ERA IN ONCOLOGY
Keywords:
Keywords. Artificial intelligence; Cancer detection; Oncology; Machine learning; Imaging diagnostics; Early diagnosis; Healthcare technology.Abstract
Abstract. Artificial Intelligence (AI) has emerged as a transformative tool in the
field of oncology, particularly in the early detection of cancer. By enhancing diagnostic
accuracy and enabling faster analysis of medical imaging and biomarkers, AI offers
the potential to significantly improve patient outcomes. This article reviews current
applications of AI in cancer screening, highlights clinical successes, and discusses
ethical and practical challenges associated with its implementation.
References
References
1. Esteva A et al., ‘Dermatologist-level classification of skin cancer with deep neural
networks’ (2017) Nature, 542(7639), 115–118.
2. Topol EJ, Deep Medicine: How Artificial Intelligence Can Make Healthcare
Human Again (Basic Books 2019).
3. Liu Y et al., ‘Artificial intelligence-based breast cancer nodal metastasis detection’
(2019) JAMA, 322(8), 799–809.
4. Ardila D et al., ‘End-to-end lung cancer screening with three-dimensional deep
learning on low-dose chest computed tomography’ (2019) Nature Medicine, 25(6),
954–961.
5. Hosny A et al., ‘Artificial intelligence in radiology’ (2018) Nature Reviews Cancer,
18(8), 500–510.
6. Rajpurkar P et al., ‘CheXNet: Radiologist-level pneumonia detection on chest X-
rays with deep learning’ (2017) arXiv preprint arXiv:1711.05225.
7. Yu KH et al., ‘Predicting non-small cell lung cancer prognosis by fully automated
microscopic pathology image features’ (2016) Nature Communications, 7, 12474.
8. Price WN II and Cohen IG, ‘Privacy in the age of medical big data’ (2019) Nature
Medicine, 25(1), 37–43.
