Results 151 to 160 of about 44,416 (264)

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

Environmental impact of computer-aided diagnosis in colonoscopy: a carbon footprint assessment of a prospective study cohort. [PDF]

open access: yesEndoscopy
Olabintan O   +20 more
europepmc   +1 more source

Frailty Predicts Incident Osteoporotic Fractures in Veterans with Rheumatoid Arthritis

open access: yesArthritis Care &Research, EarlyView.
Objective Rheumatoid arthritis (RA) is associated with an increased risk of frailty and osteoporosis, but the relationship between frailty and incident osteoporotic fractures in RA is underexplored. Methods Data were from the Veterans Affairs (VA) Rheumatoid Arthritis Registry. Frailty was measured using the VA Frailty Index (VAFI).
Katherine D. Wysham   +14 more
wiley   +1 more source

Applications of machine learning for computer-aided diagnosis of Parkinson's disease: progress and benchmark case study. [PDF]

open access: yesArtif Intell Rev
Zhang J   +7 more
europepmc   +1 more source

Determinants of Body Mass Index in Early Systemic Sclerosis: Implications for Nutritional Risk Stratification

open access: yesArthritis Care &Research, EarlyView.
Objective Gastrointestinal (GI) involvement can lead to malnutrition in patients with systemic sclerosis (SSc). Body mass index (BMI) remains the most widely used marker to screen nutritional status. We aimed to identify predictors of lower BMI in patients with SSc. Methods Patients with SSc from a prospective US cohort meeting 2013 American College of
Ali Y. Ayla   +8 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

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