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Distribution of pulmonary ventilation in women with post-COVID-19 before and after the use of a respiratory incentive device (UBICU): a pilot study
IntroductionIn the aftermath of the COVID-19 pandemic, restrictive pulmonary complications have emerged as a common long-term sequela. To address these impairments, a novel flow-based respiratory incentive device, UBICU, was developed to promote lung expansion through gamification and visual feedback. The aim of this study was to describe the pulmonary ventilation distribution using Electrical Impedance Tomography […]
Distribution of pulmonary ventilation in women with post-COVID-19 before and after the use of a respiratory incentive device (UBICU): a pilot study
IntroductionIn the aftermath of the COVID-19 pandemic, restrictive pulmonary complications have emerged as a common long-term sequela. To address these impairments, a novel flow-based respiratory incentive device, UBICU, was developed to promote lung expansion through gamification and visual feedback. The aim of this study was to describe the pulmonary ventilation distribution using Electrical Impedance Tomography […]
Maccabi-RED, mHealth innovation in community emergency care: a 4-year analysis of adoption patterns and impact on healthcare utilization
IntroductionEmergency department overcrowding due to non-urgent visits places a considerable burden on the healthcare system. Mobile health (mHealth) technologies offer potential solutions by providing community-based alternatives for emergency care.MethodsIn this study, we analyzed 4 years of implementation data from Maccabi-RED, a smartphone app-based emergency care service launched in 2019 by Israel’s second-largest healthcare maintenance organization. […]
Maccabi-RED, mHealth innovation in community emergency care: a 4-year analysis of adoption patterns and impact on healthcare utilization
IntroductionEmergency department overcrowding due to non-urgent visits places a considerable burden on the healthcare system. Mobile health (mHealth) technologies offer potential solutions by providing community-based alternatives for emergency care.MethodsIn this study, we analyzed 4 years of implementation data from Maccabi-RED, a smartphone app-based emergency care service launched in 2019 by Israel’s second-largest healthcare maintenance organization. […]
ChatGPT for diabetes education: potential, accuracy, and accessibility in patient support
BackgroundDiabetes mellitus is a chronic metabolic disease with rising global prevalence. Adequate patient education is essential to encourage self-management and reduce complications. Artificial intelligence applications such as ChatGPT have emerged as potential supplementary resources for patient education alongside the broader integration of technology in healthcare.MethodsA cross-sectional evaluation was conducted using ten frequently asked questions (FAQs) […]
ChatGPT for diabetes education: potential, accuracy, and accessibility in patient support
BackgroundDiabetes mellitus is a chronic metabolic disease with rising global prevalence. Adequate patient education is essential to encourage self-management and reduce complications. Artificial intelligence applications such as ChatGPT have emerged as potential supplementary resources for patient education alongside the broader integration of technology in healthcare.MethodsA cross-sectional evaluation was conducted using ten frequently asked questions (FAQs) […]
Quantum-SpinalNet: a hybrid deep learning approach for mammographic breast cancer detection
IntroductionBreast cancer diagnosis in mammograms remains challenging due to limitations in preprocessing, accurate differentiation of benign and malignant cases, and precise tumor segmentation.MethodsWe propose Quantum-SpinalNet, a hybrid deep learning model combining Swin ResUNet3+ for tumor segmentation with a Deep Quantum Neural Network (DQNN) and SpinalNet for classification. Preprocessing involves CEAMF-based denoising, Z-score normalization, and context-aware […]
Quantum-SpinalNet: a hybrid deep learning approach for mammographic breast cancer detection
IntroductionBreast cancer diagnosis in mammograms remains challenging due to limitations in preprocessing, accurate differentiation of benign and malignant cases, and precise tumor segmentation.MethodsWe propose Quantum-SpinalNet, a hybrid deep learning model combining Swin ResUNet3+ for tumor segmentation with a Deep Quantum Neural Network (DQNN) and SpinalNet for classification. Preprocessing involves CEAMF-based denoising, Z-score normalization, and context-aware […]
Reporting Horizon Scanning Studies: Prototype Development Study
Background: Horizon scanning identifies weak signals of innovation to anticipate future developments, providing strategic value for health care decision-making. Unlike evidence synthesis, it addresses emerging and uncertain areas but lacks standardized reporting guidance, limiting transparency, consistency, and impact. Inconsistent terminology and poorly described methods hinder comparability and uptake of findings. Objective: This study aimed to […]
Accuracy of Visual Inspection Alone to Assess Joint Effusions of the Hand: Cross-Sectional Study
Background: Physical examination is the cornerstone of diagnosing and monitoring inflammatory arthritis, with the detection of joint effusions being one of the most crucial components of the examination. Rheumatologists largely rely on palpation, supported by other examination techniques, such as evaluating the range of motion and visual inspection, to assess signs of joint swelling. However, […]
Accuracy of Deep Learning for Detecting Axillary Lymph Node Metastasis in Breast Cancer: Systematic Review and Meta-Analysis
Background: Axillary lymph node metastasis (ALNM) is an important factor in detecting breast cancer (BC). However, the noninvasive diagnosis of ALNM remains challenging. While some deep learning (DL) models have been developed for preoperative ALNM assessment, their performance lacks systematic evaluation. Objective: This study aims to evaluate the effectiveness of DL in detecting ALNM, providing […]