Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this wor...
Background: Musculoskeletal (MSK) symptoms are the leading contributor to various diseases and disability, affecting around 1.7 billion people globally. Early disease stratification is important to ensure appropriate ...
Background: Musculoskeletal (MSK) symptoms are the leading contributor to various diseases and disability, affecting around 1.7 billion people globally. Early disease stratification is important to ensure appropriate and timely care (most suited healthcare provider and best treatment choice). Currently the patient journey to diagnosis and effective treatment is long and inefficient, resulting in persistent disease burden and economic loss. Suboptimal care is due to inadequate access to healthcare, insufficiently understood disease etiology, similar symptoms of different diseases, lack of discriminatory tests and a trial-and-error approach in treatment. Objectives: SPIDeRR aims to disentangle the real-life complexity of early diagnosis of musculoskeletal problems in general, and rheumatic diseases in particular, by considering the complete picture of factors influencing patients’ symptoms. It is a unique and first-in-kind consortium of 18 partners that connects all stakeholders including academic institutions, foundations/networks (o.a. patient organization) and biotech companies within Europe. Methods: SPIDeRR’s approach goes well beyond the state-of-the-art by: - developing novel high throughput methods to analyze high dimensional multimodal clinical and biologic data from various European healthcare systems to capture and predict patient trajectory towards Rheumatic disease diagnosis. - generating supervised machine learning models that facilitate patient stratification with/without rheumatic diseases underlying similar symptoms through integration of all relevant data dimensions (symptoms, comorbidities, social circumstances, electronic health records (EHR), biomarkers and genetics) from different healthcare levels (primary and secondary care as well as patients independently seeking advice online). - expediting diagnosis through integration of patients’ clinical and biological data and enabling physicians to promptly choose a personalized therapy, which will tak
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