In the predawn hours of August 19, 2024, bolts of lightning began to fork through the purple-black clouds above the Mediterranean. From the rail of a 184-foot vessel, a 22-year-old named Matthew ...

Abstract: While analyzing large clinical datasets allows for the identification of complex patterns to achieve increased risk prediction accuracy, it also presents challenges for existing risk ...

Left to right: Tamás Darvas, Amalia Olivera Riley, Indrajit Lahiri, Richard Wien, Lucy Flesch, Mary Jane Elmore, Michael Goodrich, Sonia Nasr, Peter Mueller, and Michael Roscoe. Photos by Tate Kirgiss ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

Abstract: We consider two examples of statistical inference for two related populations. In one example we characterize two patient populations that are relevant in the construction of a clinical ...

Patients were stratified to cohort A (unspecified tumors) or cohort B (rare genomic alterations). The TARGET-CRM design permits cohort B patients to immediately enroll at one dose level below the ...

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...

The prevalent approach to motif analysis seeks to describe the local connectivity structure of networks by identifying subgraph patterns that appear significantly more often in a network then expected ...