The proceedings contain 29 papers. The topics discussed include: imputation strategies under clinical presence: impact on algorithmic fairness; predicting treatment adherence of tuberculosis patients at scale; distributionally robust survival analysis: a novel fairness loss without demographics; feature allocation approach for multimorbidity trajectory modelling; towards cross-modal causal structure and representation learning; identifying heterogeneous treatment effects in multiple outcomes using joint confidence intervals; meta-analysis of individualized treatment rules via sign-coherency; extend and explain: interpreting very long language models; neurodevelopmental phenotype prediction: a state-of-the-art deep learning model; and analyzing the effectiveness of a generative model for semi-supervised medical image segmentation.
Proceedings of the 2nd Machine Learning for Health symposium, ML4H 2022
Antonio Parziale;
2022-01-01
Abstract
The proceedings contain 29 papers. The topics discussed include: imputation strategies under clinical presence: impact on algorithmic fairness; predicting treatment adherence of tuberculosis patients at scale; distributionally robust survival analysis: a novel fairness loss without demographics; feature allocation approach for multimorbidity trajectory modelling; towards cross-modal causal structure and representation learning; identifying heterogeneous treatment effects in multiple outcomes using joint confidence intervals; meta-analysis of individualized treatment rules via sign-coherency; extend and explain: interpreting very long language models; neurodevelopmental phenotype prediction: a state-of-the-art deep learning model; and analyzing the effectiveness of a generative model for semi-supervised medical image segmentation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
