Automated classification of exposure and encourage events in speech data from pediatric OCD treatment. [PDF]
Lossio-Ventura JA +10 more
europepmc +1 more source
Local evaluation Sure Start Newcastle East: service delivery in breastfeeding, smoking, cessation and speech and language development [PDF]
Parks, Judith, Powell, Suzanne
core
New Onset of Fibromyalgia After Exposure to a Combat Environment: A Longitudinal Cohort Study
Objective Traumatic life events are hypothesized to be triggers for the onset of fibromyalgia. Posttraumatic stress disorder (PTSD) is a common comorbidity of fibromyalgia. However, limited prospective data are available on the development of fibromyalgia after exposure to high‐magnitude stress.
Jay B. Higgs +15 more
wiley +1 more source
Use of physical activity by occupational therapists and speech-language therapists in KwaZulu-Natal. [PDF]
Makaula O, Msomi NL, Ross AJ.
europepmc +1 more source
Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel +6 more
wiley +1 more source
Remote CI Fitting in Early Rehabilitation Phase: Preliminary Results. [PDF]
Homans NC +3 more
europepmc +1 more source
A programmable interpenetrating double‐network architecture, created via 3D‐TIPS printing and resin infusion, synergistically combines thermoplastic and thermosetting elastomers to balance structural rigidity and surface softness—crucial for paediatric laryngeal stents.
Elizabeth F. Maughan +14 more
wiley +1 more source
Designing socially assistive robots for clinical practice: insights from an asynchronous remote community of speech-language pathologists. [PDF]
Oliva D +4 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

