BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant dispa...
BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to...
OBJECTIVE: Depression in older adults is a growing public health concern, yet there is still a lack of convenient and real-time methods for depressive symptoms identification. This study aims to develop a gait-based depression recognition method for ...
Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive manual interpretation as well as unavoidable interpreter-dependent variabilities. We propose artific...
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under-e...
Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the...
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...
BACKGROUND: The rising prevalence of dementia is a major concern, with approximately 45% of cases linked to 14 modifiable risk factors. The European project LETHE aims to develop a personalized digital intervention model to delay or prevent cognitive...
The study aimed to develop an AI-assisted ultrasound model for early liver trauma identification, using data from Bama miniature pigs and patients in Beijing, China. A deep learning model was created and fine-tuned with animal and clinical data, achi...
To propose a deep learning model and explore its performance in the auxiliary diagnosis of lung cancer associated with cystic airspaces (LCCA) in computed tomography (CT) images. This study is a retrospective analysis that incorporated a total of 342...
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