Results 131 to 140 of about 21,280,601 (295)
Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett +8 more
wiley +1 more source
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah +5 more
wiley +1 more source
Human-Guided Learning for Probabilistic Logic Models
Advice-giving has been long explored in the artificial intelligence community to build robust learning algorithms when the data is noisy, incorrect or even insufficient. While logic based systems were effectively used in building expert systems, the role
Phillip Odom, Sriraam Natarajan
doaj +1 more source
Very recently, the unexpected combination of data structures and machine learning has led to the development of a new area of research, called learned data structures. Their distinguishing trait is the ability to reveal and exploit patterns and trends in the input data for achieving more efficiency in time and space, compared to previously known data ...
Paolo Ferragina, Giorgio Vinciguerra
openaire +2 more sources
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim +18 more
wiley +1 more source
Dirichlet belief networks for topic structure learning
Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to leverage the ...
Buntine, Wray +3 more
core
Objective Australian evidence on lived and care experiences of chronic musculoskeletal shoulder pain (CMSP), irrespective of disorder classification or disease, is limited. However, such evidence is important for person‐centered care and informing local service pathways and care guidelines or standards.
Sonia Ranelli +8 more
wiley +1 more source
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg +26 more
wiley +1 more source
Bayesian Learning of Sum-Product Networks
Sum-product networks (SPNs) are flexible density estimators and have received significant attention due to their attractive inference properties. While parameter learning in SPNs is well developed, structure learning leaves something to be desired: Even ...
Ge, Hong +4 more
core
Objective We conducted formative research aimed at identifying solutions that address inequitable health outcomes in lupus due to adverse social determinants of health (SDoH). Methods We conducted a search for keywords, which provided insights into potential solutions and initiatives underway. An advisory panel of lupus experts iteratively reviewed the
Joy Buie +11 more
wiley +1 more source

