Reliable machine learning models in genomic medicine using conformal prediction
Christina Papangelou,
Konstantinos Kyriakidis,
Pantelis Natsiavas
et al.
Abstract:Machine learning and genomic medicine are the mainstays of research in delivering personalized healthcare services for disease diagnosis, risk stratification, tailored treatment, and prediction of adverse effects. However, potential prediction errors in healthcare services can have life-threatening impact, raising reasonable skepticism about whether these applications are beneficial in real-world clinical practices. Conformal prediction is a versatile method that mitigates the risks of singleton predictions by… Show more
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