Does artificial intelligence have a place in precision oncology?
Applications in artificial intelligence have the potential to transform precision oncology, but data quality and clinical validation of tools are still challenging
Applications in artificial intelligence have the potential to transform precision oncology, but data quality and clinical validation of tools are still challenging
Using treatments only where clear benefit has been demonstrated and modulating doses based on evidence are potentially effective strategies to reduce the rising costs of oncology
The rapidly increasing integration of AI into many aspects of breast cancer management calls for urgent definition of expected levels of evidence and bespoke regulatory and reimbursement processes
A study proposes a model that is able to learn broad aspects of cancer–immune interactions from early phase trial data
ESMO is advocating for secondary and tertiary care levels to be included into international agreements and WHO’s documents to respond to pandemics
In the period 2024-2026, the technical collaboration between the United Nations agency and the Society plans a series of evidence-based activities to improve global cancer care
Well-designed real-world observational studies are hypothesis-generating and impact therapeutic decisions
The two Pan-Asian Guideline Adaptations of parental ESMO Clinical Practice Guidelines reflect the younger age of disease occurrence and lack of some treatment data in Asia
Several ESMO initiatives highlight the need for closing the gap between fast cancer research and a lack of accessibility to treatments in the real world
Recent studies show how digital health apps enhance the patient experience, and improve multiple quality of life domains and in some cases, adherence to treatment, but their integration into the healthcare system is still a challenge
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