Dec 2, 2022
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Synthetic medical data – needed to bring ML in medicine up to speed? To bring medical AI to the next level, in terms of exceeding state-of-art and not just developing but also implementing novel algorithms as decision support tools into clinical practice, we need to bring data scientists, laboratory scientists and physician (researchers) together. To succeed with this, we need to bring medical data out in the open, to benefit from the best possible models being developed jointly by the data science community. Solving the data privacy issues – in terms of creating synthetic data sets reflecting the correlations of the original data sets without jeopardizing data privacy – is needed. Here you get the perspectives on real clinical challenges, real data science approaches being implemented into clinical practice, regulatory issues and real unmet needs of synthetic data sets from the perspective of a physician researcher.Synthetic medical data – needed to bring ML in medicine up to speed? To bring medical AI to the next level, in terms of exceeding state-of-art and not just developing but also implementing novel algorithms as decision support tools into clinical practice, we need to bring data scientists, laboratory scientists and physician (researchers) together. To succeed with this, we need to bring medical data out in the open, to benefit from the best possible models being developed jointly by the data scie…
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