AI tool outperforms manual PD-L1 scoring in a study
Integrating artificial intelligence into pathology routine workflows could optimise patient selection for immunotherapy
Integrating artificial intelligence into pathology routine workflows could optimise patient selection for immunotherapy
In a newly released framework paper, ESMO defines criteria for assessing and implementing AI-based biomarkers in oncology
Extensive research is focusing on the development of tools that may enhance drug development and personalised oncology in the near future
As a proof of concept, an AI-powered large language model matching platform shows promise in patient selection
While synthetic real-world data may help overcome current challenges in clinical trials, it also introduces new complexities
Findings from latest research reflect emerging opportunities in oncology to refine treatments by challenging current paradigms of care
Findings from four studies provide further evidence on the potential of AI-driven pathology, imaging and multiomic data to guide clinical decision-making
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
The ELCAP statements, developed by a group of international experts, help oncology stakeholders recognise the opportunities and the risks of these artificial intelligence systems by categorising them into three types
Study findings reveal that good thymic health, based on an AI-derived algorithm, is associated with improved survival after immunotherapy in different tumour types
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