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This is a retrospective, observational, single-center study conducted at the Hematology Unit of the IRCCS Azienda Ospedaliero-Universitaria di Bologna. The study aims to integrate genomic, clinical, and imaging data-all previously collected and pseudonymized-from earlier spontaneous studies carried out by the Hematology Unit. The main goal is to explore how genetic, clinical, and imaging features relate to disease outcomes and to develop predictive models using artificial intelligence (AI) and machine learning (ML). These models may help forecast disease progression and treatment response in the future. By combining different types of data, the research team hopes to develop new methods to predict disease progression and treatment outcomes. No new procedures, tests, or patient visits are required for this study. All the information analyzed will come from existing data collected as part of past clinical practice or previous research projects. Once anonymized, it will no longer be possible to identify individual patients. The anonymized dataset will be securely developed and stored by the bioinformatics team at the Hematology Unit of IRCCS AOUBO.
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Carolina Terragna, MD
Data sourced from clinicaltrials.gov
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