Abstract:In this paper, a suitable and interpretable diagnosis statistical model is proposed to predict the Non-Alcoholic Steatohepatitis (NASH) from near infrared spectrometry data. In this disease, unknown patients profiles are expected to lead to different diagnosis. The model has then to take into account the heterogeneity of the data and the dimension of the spectrometric data. To this end, we propose to fit a mixture on the joint distribution of the diagnosis binary variable and the covariates selected in the spe… Show more
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