KATY: enabling clinicians and clinical researchers to make better therapy decisions for people with cancer
A PROJECT FOR: European Union (Horizon2020 program)
Personalized medicine holds the promise to find tailored, targeted, nearly ‘hand-made’ cures for patients. In fact, artificial intelligence (AI) promises a new paradigm for healthcare. However, there is still a gap between AI data and medical application. The KATY project aims to bridge this gap by developing an AI-empowered personalized medicine system to bring easy-to-understand and ready-to-use AI data to the fingertips of clinicians and clinical researchers.
With the aim of developing such a powerful tool in diagnosing and treating complex conditions, the KATY project centers its efforts on data from one of the most dangerous cancers: clear cell renal cell carcinoma. The gathering and cataloguing of molecular, biological and clinical knowledge are essential steps to develop the necessary Knowledge graphs and AI-models. The KATY Project will build a precise personalized medicine system empowered by trusted and explainable AI to provide a predictive system to clinicians for supporting them in the decision of treatment recommendations with a patient-centric approach. The resulting services will be tested and evaluated in pilot sites across Europe to assess their usability, performance and utility.
The envisioned result
The tool has the potential to identify new (molecular) evidence on the predictive value of AI solutions. Hence, KATY seeks to enable clinicians and clinical researchers to make better therapy decisions for people with one of the most dangerous cancers, clear cell renal cell carcinoma (ccRCC).
The role of PredictBy, as experts in Experimental Design and Evaluation,
Consists of conducting the following tasks:
Cost-effectiveness analysis of the interventions: we assess whether the potential impact that the two front-end displays, developed in an earlier phase of the project, indeed enrich clinical research, clinical practice and patient understanding around prognosis and the potential of various therapeutic options.
Policy and socio-economic impact evaluation: we analyze the socio-economic impact of AI interventions at healthcare system level, including all stakeholders involved in the process of AI development and use (health professionals).