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Clinical Data Science

…conducts research into improvements in decision making at all stages of patient interaction with the healthcare systems: analysis of data to provide differential diagnoses with predictions of uncertainty, data-driven estimation of risks of future morbidity, utilisation of patient-specific data to determine the optimal path of treatment considering also predictions of treatment side effects, optimising risks and benefits of hospitalizations, and treatment monitoring – analysis of therapy effectiveness indicators or outcomes in treatment management. Cooperation with the Personal Health research strand will bring advances in real-time treatment data analysis to provide recommendations about effectiveness and the likelihood of success based on patient-specific data.

 The decision support AI will use data science machine learning and deep learning models based on a combination of one or more of the following patient-specific data types: patient presentation, medical history, laboratory results, clinical notes, medical imaging data, molecular biology data, socioeconomic factors, patient-specific simulation data, and other available relevant data.

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