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Application of artificial intelligence in the health management of chronic disease: bibliometric analysis.
Front Med (Lausanne)
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School of Nursing, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
Background: With the rising global burden of chronic diseases, traditional health management models are encountering significant challenges. The integration of artificial intelligence (AI) into chronic disease management has enhanced patient care efficiency, optimized treatment strategies, and reduced healthcare costs, providing innovative solutions in this field. However, current research remains fragmented and lacks systematic, comprehensive analysis.
View Article and Find Full Text PDFLeveraging Smart Telemedicine Technology to Enhance Nursing Care Satisfaction and Revolutionize COVID-19 Care: Prospective Cohort Study.
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Department of Cardiovascular Medicine, Fu Jen Catholic University Hospital, New Taipei, Taiwan.
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View Article and Find Full Text PDFProtocol for the enhanced management of multimorbid patients with COPD and severe asthma: role of indoor air quality.
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Fundació de Recerca Clínic Barcelona - Institut d'Investigacions Biomèdiques August Pi i Sunyer (FRCB-IDIBAPS), Barcelona, Spain.
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View Article and Find Full Text PDFSelf-Efficacy in Hypertension Management Using e-Health Technology: A Randomized Controlled Trial in Primary Care.
J Clin Hypertens (Greenwich)
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Center for Primary Health Care Research, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.
Self-efficacy is tightly intertwined with person-centered care and correlates with engaging in self-care behaviors, an important part of hypertension treatment. Evidence indicates that e-Health-based self-management interventions could increase self-efficacy. The objectives of this study were to investigate whether an intervention with a person-centered approach supported by e-Health technology can impact self-efficacy.
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