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In the medical field, endoscopic video analysis is crucial for disease diagnosis and minimally invasive surgery. The Endoscopic Foundation Models (Endo- FM) utilize large-scale self-supervised pre-training on endoscopic video data and leverage video transformer models to capture long-range spatiotemporal dependencies. However, detecting complex lesions such as gastrointestinal metaplasia (GIM) in endoscopic videos remains challenging due to unclear boundaries and indistinct features, and Endo-FM has not demonstrated good performance.

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Background: Advancements in mobile technology have paved the way for innovative interventions aimed at promoting physical activity (PA).

Objective: The main objective of this feasibility study was to assess the feasibility, usability, and acceptability of the More In Action (MIA) app, designed to promote PA among older adults. MIA offers 7 features: personalized tips, PA literacy, guided peer workouts, a community calendar, a personal activity diary, a progression monitor, and a chatbot.

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Background: Digital gaming has become increasingly popular among older adults, potentially offering cognitive, social, and physical benefits. However, its broader impact on health and well-being, particularly in real-world settings, remains unclear.

Objective: This study aimed to evaluate the multidimensional effects of digital gaming on health and well-being among older adults, using data from the Japan Gerontological Evaluation Study conducted in Matsudo City, Chiba, Japan.

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Background: Telemedicine is transforming health care by enabling remote diagnosis, consultation, and treatment. Despite rapid adoption during the COVID-19 pandemic, telemedicine uptake among health care professionals (HCPs) remains inconsistent due to perceived risks and lack of tailored policies. Existing studies focus on patient perspectives or general adoption factors, neglecting the complex interplay of contextual variables and trust constructs influencing HCPs' telemedicine adoption.

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Patients with anterior cruciate ligament reconstruction frequently present asymmetries in the sagittal plane dynamics when performing single leg jumps but their assessment is inaccessible to health-care professionals as it requires a complex and expensive system. With the development of deep learning methods for human pose detection, kinematics can be quantified based on a video and this study aimed to investigate whether a relatively simple 2D multibody model could predict relevant dynamic biomarkers based on the kinematics using inverse dynamics. Six participants performed ten vertical and forward single leg hops while the kinematics and the ground reaction force "GRF" were captured using an optoelectronic system coupled with a force platform.

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