How artificial intelligence is changing oncology

New AI models are now analysing huge amounts of biological data and recognising patterns that would have required years of experimentation in the laboratory. Research teams from Google, DeepMind and Microsoft are developing systems that can predict how tumours will react to certain therapies from single-cell data or tissue samples. In some cases, hypotheses proposed by AI have already been confirmed experimentally. The field of cancer diagnostics is also changing. Modern algorithms analyse medical images or digital tissue samples with an accuracy that is sometimes comparable to that of experienced pathologists. Companies such as PathAI and Aiforia are developing platforms that automate pathology and image analysis and support clinical decisions. At the same time, new approaches for early diagnosis are emerging. Biotech companies such as Freenome are combining blood tests with AI to detect cancer at a very early stage. Other companies are analysing DNA fragments in the blood and identifying characteristic patterns of different tumour types. This is creating a new, data-driven oncology in which computers combine modelling, diagnostics, therapy development and clinical decisions. For cancer medicine, this marks the beginning of a phase in which data analysis and biology are increasingly merging.