Results 111 to 120 of about 374,519 (265)

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein   +7 more
wiley   +1 more source

Immunosuppressive Drug Use in Limited Systemic Sclerosis: An International Survey

open access: yesArthritis Care &Research, EarlyView.
Objective Current guidelines recommend immunosuppressive treatment for diffuse cutaneous systemic sclerosis but are less clear on their use in limited cutaneous systemic sclerosis (lcSSc) in the absence of internal organ complications. We conducted an international survey to understand current immunosuppressive drug prescribing patterns in lcSSc ...
Sabrina Hoa   +3 more
wiley   +1 more source

Real‐World Safety and Effectiveness of JAK Inhibitors in Systemic Sclerosis: A Propensity‐Matched Study From the EUSTAR Cohort

open access: yesArthritis Care &Research, EarlyView.
Objective JAK inhibitors (JAKi) have shown promising effects in early‐phase studies of systemic sclerosis (SSc). We aimed to assess the safety and explore the effectiveness of JAKi compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the European Scleroderma Trials and Research Group (EUSTAR) cohort was ...
Stefano Di Donato   +27 more
wiley   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

open access: yesArthritis Care &Research, EarlyView.
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

CHANNELS AND DETERMINANTS OF TECHNOLOGY DIFFUSION

open access: yesContemporary Economy, 2015
Potential for development of all countries of modern World is highly dependent on the ability to create and absorb technology. The following paper constitutes review of the literature focused on channels and factors that determine speed of this process ...
Jakub M. Kwiatkowski
doaj  

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

open access: yesArthritis 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   +7 more
wiley   +1 more source

Technology diffusion and prostate cancer quality of care. [PDF]

open access: yesUrology, 2014
Schroeck FR   +5 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational 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   +3 more
wiley   +1 more source

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