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Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model. (arXiv:2205.13085v1 [stat.ML])
May 27, 2022, 1:11 a.m. | Eric V. Strobl, Thomas A. Lasko
stat.ML updates on arXiv.org arxiv.org
Complex diseases are caused by a multitude of factors that may differ between
patients even within the same diagnostic category. A few underlying root causes
may nevertheless initiate the development of disease within each patient. We
therefore focus on identifying patient-specific root causes of disease, which
we equate to the sample-specific predictivity of the exogenous error terms in a
structural equation model. We generalize from the linear setting to the
heteroscedastic noise model where $Y = m(X) + \varepsilon\sigma(X)$ with …
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