Results 161 to 170 of about 146,329 (252)
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah +4 more
wiley +1 more source
ANNalog: generation of MedChem-similar molecules. [PDF]
Dai W +4 more
europepmc +1 more source
Objective The diagnosis of fibromyalgia (FM) is challenging due to the absence of definitive biomarkers, numerous overlapping comorbidities, and its reliance on patient‐reported symptoms. Discrepancies between diagnostic criteria and clinical practice imply the possibility of diagnostic biases, complicating timely and accurate identification.
Sung‐A Kim +2 more
wiley +1 more source
BioNeuralNet: a graph neural network based Multi-Omics network data analysis tool. [PDF]
Ramos V +8 more
europepmc +1 more source
Objective To investigate the association between frailty and cancer incidence and mortality in patients with rheumatoid arthritis (RA). The study aimed to identify how frailty influences cancer risk, and cancer‐specific outcomes. Methods This retrospective cohort study analyzed data from the Veterans Affairs Rheumatoid Arthritis (VARA) registry (2002 ...
Bhavik Bansal +12 more
wiley +1 more source
The Role of Artificial Intelligence in Preservice Science Teachers' Analogical Reasoning: Evidence from Analogy Design. [PDF]
Zorlu F.
europepmc +1 more source
Automated Hand Flexor Tendon Thickness Measurement in Systemic Sclerosis
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasound and measured manually, a time‐consuming process prone to inter‐observer variability.
Mark Greveling +4 more
wiley +1 more source
BDI-Kit: An AI-powered toolkit for biomedical data harmonization. [PDF]
Lopez R, Santos A, Koutras C, Freire J.
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Molecular deep learning at the edge of chemical space. [PDF]
van Tilborg D, Rossen L, Grisoni F.
europepmc +1 more source

