Recent findings show digital tools have the potential to improve the monitoring of symptoms and psychological aspects, but they should be integrated within routine clinical practice
Growing evidence shows that AI models can predict a patient's disease trajectory and signal the need for early therapeutic intervention
The innovative approach was successfully tested on NY-ESO-1 and promises to bypass some current challenges in the identification of T cell receptors for therapeutic use
Research shows that widespread use of artificial intelligence tools is associated with high demand for energy, water and minerals
Diverse approaches are investigated in oncology that also include the use of artificial intelligence
While the use of artificial intelligence systems is expanding in oncology, ethical issues including biases introduced in care delivery and uneven access to technology raise concerns about whether some patients may be left behind
The ESMO-Magnitude of Clinical Benefit Scale has been enhanced to address critical aspects of modern oncology trials, such as novel study designs, quality of life and long-term survival benefits
Additional treatment targets and potentially repurposable agents were identified based on chemoradiotherapy response, which could now be explored for further validation.
Evidence is growing for a potential role of microplastics in cancer development, but more solid research is needed
While many models and tools are designed to support clinical decision-making, AI is already serving cancer research for background tasks, with some potential to educate patients too
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