Results 181 to 190 of about 11,733,399 (339)
A Pilot Study of Cefepime and Meropenem Therapeutic Drug Monitoring in Pediatric Patients on Extracorporeal Therapy. [PDF]
McFarland KM +3 more
europepmc +1 more source
Clinical, histological, and serological predictors of renal function loss in lupus nephritis.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang +21 more
wiley +1 more source
Accounting for sensitivity of latent learning to behavioral statistics with successor representations. [PDF]
Menezes M, Zeng X, Cheng S.
europepmc +1 more source
Over the past 50 years, the science of pediatric rheumatology has grown exponentially due to an expansion in the understanding of complex rheumatic conditions and a surge in novel targeted therapeutics. Physician‐scientists in the field of pediatric rheumatology have played major roles in these advancements that have improved the care of children ...
Ekemini A. Ogbu +2 more
wiley +1 more source
The impact of goal orientation on Chinese university students' reading engagement: the mediating roles of boredom and self-efficacy. [PDF]
Hung LC, Lin X, Hung MT, Smith CS.
europepmc +1 more source
Goal-directed resuscitation for patients with early septic shock.
S. Peake +10 more
semanticscholar +1 more source
Objective Studies of damage accrual in patients with systemic lupus erythematosus (SLE) show associations with disease activity measured by the SLE Disease Activity Index 2000 (SLEDAI‐2K), but these associations are imperfect. SLEDAI scores are powerfully influenced by weightings (1‐8) assigned to each domain.
Kevin Zhang +8 more
wiley +1 more source
Coaching presence as the foundation for the working alliance in AI coaching. [PDF]
Nam GY, Choi J.
europepmc +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source

