Results 131 to 140 of about 561,945 (263)

Determinants of Body Mass Index in Early Systemic Sclerosis: Implications for Nutritional Risk Stratification

Arthritis Care &Research, EarlyView.
Objective Gastrointestinal (GI) involvement can lead to malnutrition in patients with systemic sclerosis (SSc). Body mass index (BMI) remains the most widely used marker to screen nutritional status. We aimed to identify predictors of lower BMI in patients with SSc. Methods Patients with SSc from a prospective US cohort meeting 2013 American College of
Ali Y. Ayla, Meng Zhang, Bingrui Chen, Claudia Pedroza, Brian Skaug, Maureen Mayes, Michael Hughes, Shervin Assassi, Zsuzsanna H. McMahan   +8 more
wiley   +1 more source

Optimizing HIV Interventions for Multiplex Social Networks via Partition-Based Random Search. [PDF]

IEEE Trans Cybern, 2018
Zhang Q, Zhong L, Gao S, Li X.
europepmc   +1 more source

Understanding the Burden of Orofacial Involvement and Patient Treatment Preferences in Systemic Sclerosis: Results From a Large International Survey

Arthritis Care &Research, EarlyView.
Objective Orofacial manifestations are significantly impactful in patients with systemic sclerosis (SSc) yet remain understudied, with no dedicated clinical guidelines to inform their management. Methods An international online survey comprised38 questions addressing orofacial manifestations of SSc, including patients’ confidence in their treating ...
Eleni Deligianni, Lee Shapiro, Deana Gibbs, Zsuzsanna H. McMahan, Michael Hughes   +4 more
wiley   +1 more source

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

An adaptive random search for short term generation scheduling with network constraints. [PDF]

PLoS One, 2017
Marmolejo JA, Velasco J, Selley HJ.
europepmc   +1 more source

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

Normal and tumoral melanocytes exhibit q-Gaussian random search patterns. [PDF]

PLoS One, 2014
da Silva PC, Rosembach TV, Santos AA, Rocha MS, Martins ML.   +4 more
europepmc   +1 more source

Facial Cosmetic Therapy Use Among Patients With Systemic Sclerosis: An Australian Cohort Study

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) is associated with numerous facial manifestations for which patients may engage in cosmetic therapies. It is unclear how patients with SSc use these therapies. This study sought to characterize patient engagement and experiences with cosmetic therapies for SSc‐related and non‐SSc–related facial changes.
Zachary Warren, Diane Apostolopoulos, Gene‐Siew Ngian, Amanda M. Saracino, Laura Ross, Nava Ferdowsi, Jennifer Walker, Cindy Hall, Kim Griggs, Susanna Proudman, Wendy Stevens, Joanne Sahhar   +11 more
wiley   +1 more source

Random search algorithm for solving the nonlinear Fredholm integral equations of the second kind. [PDF]

PLoS One, 2014
Hong Z, Yan Z, Yan J.
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source