Background Digital adherence technologies (DATs) with associated differentiated care are potential tools to improve ...

Assessing elimination of malaria locally requires a surveillance system with high sensitivity and specificity to detect its ...

MBTL improves deep reinforcement learning by optimizing task selection, boosting sample efficiency and adaptability in ...

A data-fusion-model method for state of health estimation of Li-ion battery packs based on partial charging curve. view more ...

Interformer, a generative deep learning model, enhances protein-ligand docking accuracy and generalizability by capturing essential non-covalent interactions. It demonstrates its practical value ...

This iterative approach to model building, sometimes referred to as a `Bayesian workflow' is seen as good practise in Bayesian data analysis literature. In the revised version of the paper, we will ...

This study proposes an important new approach to analyzing cell-count data that are often undersampled and cannot be correctly assessed with traditional statistical analyses. The presented case ...

However, the divergence computation and normalization constraints are challenging for model implementation. To navigate these challenges, the Bayesian inference problem is transformed into an ...

A research team behind a new study at the Hebrew University of Jerusalem has made an important breakthrough in understanding how immune cells known as T cells are activated. By using an innovative ...

Search Engine Land » PPC » Why marketing mix modeling is crucial in 2025 and beyond Chat with SearchBot Please note that your conversations will be recorded. In an era where privacy concerns ...