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Background: Barriers to mental health assessment and intervention have been well documented within South Africa, in both urban and rural settings. Internationally, evidence has emerged for the effectiveness of technology and, specifically, app-based mental health tools and interventions to help overcome some of these barriers. However, research on digital interventions specific to the South African context and mental health is limited.

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Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.

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Background And Objectives: Patients with multiple sclerosis (MS) may demonstrate better disease control when treatment is initiated on high-efficacy disease-modifying therapies (DMTs) from onset. This subgroup analysis assessed the long-term efficacy and safety profile of the high-efficacy DMT ocrelizumab (OCR) as first-line therapy for early-stage relapsing MS (RMS).

Methods: Post hoc exploratory analyses of efficacy and safety were performed in a subgroup of treatment-naive patients with RMS who received ≥1 dose of OCR in the multicenter OPERA I/II (NCT01247324/NCT01412333) studies.

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The impact of cognitive decline in older adults can be evaluated with dual-task gait (DTG) testing in which a cognitive task is performed during walking, leading to increased costs of gait. Previous research demonstrated that higher DTG costs correlate with increasing cognitive deficits and with age. The present study was conducted to explore whether the relationship between the DTG costs and cognitive abilities in older individuals is influenced by sex differences.

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Video-based estimation of blood pressure.

PLoS One

January 2025

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America.

In this work, we propose a non-contact video-based approach that estimates an individual's blood pressure. The estimation of blood pressure is critical for monitoring hypertension and cardiovascular diseases such as coronary artery disease or stroke. Estimation of blood pressure is typically achieved using contact-based devices which apply pressure on the arm through a cuff.

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