Results 241 to 250 of about 520,634 (314)

Drugs induced Raynaud's phenomenon and underlying mechanism: a disproportionality analysis from the WHO pharmacovigilance database

open access: yesArthritis &Rheumatology, Accepted Article.
Objectives The aim of this study is to generate hypotheses about unknown drugs associated with the onset or worsening of Raynaud's Phenomenon (RP) and to explore their potential pathophysiological mechanisms through a mixed disproportionality/clustering analysis from the WHO pharmacovigilance database.
Alex Hlavaty   +4 more
wiley   +1 more source

Mismatching Expressions: Spatiotemporal and Kinematic Differences in Autistic and Non‐Autistic Facial Expressions

open access: yesAutism Research, EarlyView.
ABSTRACT Preliminary studies suggest there are differences in the facial expressions produced by autistic and non‐autistic individuals. However, it is unclear what specifically is different, whether such differences remain after controlling for facial morphology and alexithymia, and whether production differences relate to perception differences ...
Connor T. Keating   +3 more
wiley   +1 more source

A Bayesian network analysis of the Pfizer COVID-19 vaccine in the paediatric population. [PDF]

open access: yesNPJ Vaccines
Shukla T   +12 more
europepmc   +1 more source

From information to evidence in a Bayesian network

open access: green, 2019
Ali Ben Mrad   +3 more
openalex   +1 more source

Parental Stress and Caregiver Role Modulate Child–Caregiver Prosodic Synchrony in Autism: A Computational Analysis

open access: yesAutism Research, EarlyView.
ABSTRACT Parental stress influences parent–child interactions in typical development and is a prognostic factor of autism outcome. However, we still do not know to what extent parental stress affects parent–child interactions and whether caregiver role matters.
Maria Grazia Logrieco   +11 more
wiley   +1 more source

Generative Deep Learning for Advanced Battery Materials

open access: yesBatteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal   +3 more
wiley   +1 more source

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