Cancer Diagnosis, Accelerated by AI

Cancer remains a leading cause of death worldwide, with Asia bearing a disproportionate burden.

- Ayesha Siddiqui

In 2020, the region accounted for nearly half of global cancer cases and over 58 per cent of cancer-related deaths. Lung, breast, and colorectal cancers were the most commonly diagnosed.

Artificial intelligence (AI) has shown particular promise in early detection, where timely diagnosis can significantly improve outcomes. Today, AI supports cancer diagnosis across medical imaging, digital pathology, and genomic analysis, helping clinicians review scans, analyse tissue samples, and interpret complex data more efficiently. Studies show that AI can detect suspicious findings earlier than routine clinical review in some cases. In China, systems such as Alibaba's DAMO GRAPE and Huawei’s RuiPath have demonstrated high diagnostic accuracy and are already deployed in clinical settings. Beyond detection, machine-learning models are increasingly used to predict treatment effectiveness and patient outcomes. As World Cancer Day is observed on February 4, attention is turning to whether the rapid deployment of AI tools across the Asia-Pacific region reflects genuine clinical impact or continued technological hype.

Cancer remains one of the leading causes of death globally, with Asia carrying a disproportionate share of the burden. In 2020, the region accounted for 49.3 per cent of global cancer incidence and 58.3 per cent of global cancer mortality. The most commonly diagnosed cancers were lung cancer (13.8 per cent), breast cancer (10.8 per cent), and colorectal cancer (10.6 per cent) according to the GLOBOCAN 2020 report.

Early detection is where artificial intelligence (AI) has shown the greatest potential. AI is now used across several stages of cancer diagnosis, including medical imaging, digital pathology, and genomic and molecular analysis. It helps clinicians review scans, analyse tissue samples, and interpret large datasets more efficiently, and in some settings supports risk assessment and clinical decision-making.