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The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.

The Lancet. Rheumatology
BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratify...

Judging robot ability: How people form implicit and explicit impressions of robot competence.

Journal of experimental psychology. General
Robots' proliferation throughout society offers many opportunities and conveniences. However, our ability to effectively employ these machines relies heavily on our perceptions of their competence. In six studies (N = 2,660), participants played a co...

Machine Learning-Based Prediction of Hospitalization During Chemoradiotherapy With Daily Step Counts.

JAMA oncology
IMPORTANCE: Toxic effects of concurrent chemoradiotherapy (CRT) can cause treatment interruptions and hospitalizations, reducing treatment efficacy and increasing health care costs. Physical activity monitoring may enable early identification of pati...

Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.

JAMA internal medicine
IMPORTANCE: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioratio...

Deep Learning-based Approach for Brainstem and Ventricular MR Planimetry: Application in Patients with Progressive Supranuclear Palsy.

Radiology. Artificial intelligence
Purpose To develop a fast and fully automated deep learning (DL)-based method for the MRI planimetric segmentation and measurement of the brainstem and ventricular structures most affected in patients with progressive supranuclear palsy (PSP). Materi...

Impact of Deep Learning Image Reconstruction Methods on MRI Throughput.

Radiology. Artificial intelligence
Purpose To evaluate the effect of implementing two distinct commercially available deep learning reconstruction (DLR) algorithms on the efficiency of MRI examinations conducted in real clinical practice within an outpatient setting at a large, multic...

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Radiology. Artificial intelligence
Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized m...