Scientific Research Publishing

A Multimodal Machine-Learning Framework for Predicting Lithium-Associated Renal Dysfunction from Synthetic Biomarker Trajectories ()

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant ...
BMJ Open

Identifying common mental disorders among perinatal and non-perinatal women in northern India: a cross-sectional validation study of the diagnostic accuracy of six se…

Objectives To translate and culturally adapt six self-report measures for depression, anxiety, post-traumatic stress disorder ...
YouTube on MSN

What are the domain and range of our most basic parent functions

Learn how to determine the domain and range of a function given the graph of the function. Since the domain of a function is ...

Edgewise Therapeutics Talks Phase III Becker Readout, EDG-7500 HCM Data Due in Q2 at Conference

Executives from Edgewise Therapeutics (NASDAQ:EWTX) highlighted recent clinical updates and upcoming milestones across the ...
YouTube on MSN

Math tutorial for graphing an exponential function with transformations

👉 Learn how to graph exponential functions involving horizontal shift. An exponential function is a function that increases ...
The Lancet

Natural history of chronic hepatitis B in untreated adults without cirrhosis according to baseline hepatitis B virus DNA and alanine aminotransferase concentrations: a ...

These findings, alongside the linked systematic review and meta-analysis of antiviral treatment efficacy, supported the 2024 WHO guidelines expansion of treatment criteria to include individuals with ...
IEEE

Differentiable Weights-Varying Nonlinear MPC via Gradient-Based Policy Learning: An Autonomous Vehicle Guidance Example

Abstract: Tuning Model Predictive Control (MPC) cost weights for multiple, competing objectives is labor-intensive. Derivative-free automated methods, such as Bayesian Optimization, reduce manual ...
IEEE

Learning Gradients of Convex Functions with Monotone Gradient Networks

Abstract: While much effort has been devoted to deriving and analyzing effective convex formulations of signal processing problems, the gradients of convex functions also have critical applications ...