Unearthing experimental materials data buried in scientific papers using LLMs

Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...
IEEE

STICA: Spanning-Tree-Based Identification of Clusters With Agglomeration for Numerical Data

Abstract: Clustering is an unsupervised method used to group data points based on their similarity. It has many applications in data mining and preprocessing. Algorithms used for arbitrarily shaped ...
Colorado Public Radio

‘A culture of fear,’ outdated equipment and data manipulation. How the Colorado public health lab unraveled

Just after Christmas 2023, a chemist at the state public health laboratory admitted to her bosses that she had manipulated test results. In the coming weeks her supervisors at the Colorado Department ...
BMJ

Causal inference is hard, and advanced statistical analysis is not enough

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...
IEEE

Mitigating Missing Feature Channels at Inference Stage: Test-Time Adaptation Through Self-Training With Data Imputation

Abstract: The robustness of deep learning model can be compromised by out-of-distribution (OOD) testing data. Test-time adaptation (TTA) emerges as an efficient method to mitigate the distribution gap ...
GitHub

IHB-IBR-department/TFNBS

TFNBS Toolbox is a Python package for computation and generation of network-based statistics for neuroscience data (i.e. fMRI, EEG data). The core concept is based on eliminating the use of a ...