Shyam Visweswaran

TL;DR: In this retrospective analysis of data sets from patients with sepsis, 4 clinical phenotypes were identified that correlated with host-response patterns and clinical outcomes, and simulations suggested these phenotypes may help in understanding heterogeneity of treatment effects.

TL;DR: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics.

TL;DR: The hypothesis is that a patient-management decision that is unusual with respect to past patient care may be due to an error and that it is worthwhile to generate an alert if such a decision is encountered, and that the outlier-based alerting can lead to promising true alert rates.

TL;DR: It is concluded that representing epistatic interactions using BN models and scoring them using a BN scoring criterion holds promise for identifying epistatic genetic variants in data.

TL;DR: In this paper, the authors proposed two relaxations called the Randomized Conditional Independence Test (RCIT) and the Randomised conditional Correlation Test (RCoT) which both approximate KCIT by utilizing random Fourier features.