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http://dx.doi.org/10.3389/fdgth.2023.1329196 | DOI Listing |
J Med Internet Res
January 2025
Institute for Entrepreneurship, Technology Management and Innovation (EnTechnon), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
Background: Digital health technology (DHT) has the potential to revolutionize the health care industry by reducing costs and improving the quality of care in a sector that faces significant challenges. However, the health care industry is complex, involving numerous stakeholders, and subject to extensive regulation. Within the European Union, medical device regulations impose stringent requirements on various ventures.
View Article and Find Full Text PDFCardiol Rev
January 2025
Department of Medicine, Federal Medical and Dental College, Islamabad, Pakistan.
Recent advancements in artificial intelligence (AI) have revolutionized the diagnosis, risk assessment, and treatment of heart failure (HF). AI models have demonstrated superior performance in distinguishing healthy individuals from those at risk of congestive HF by analyzing heart rate variability data. In addition, AI clinical decision support systems exhibit high concordance rates with HF experts, enhancing diagnostic precision.
View Article and Find Full Text PDFCureus
December 2024
Pediatrics Department, Khyber Teaching Hospital, Peshawar, PAK.
Background Artificial intelligence (AI) is revolutionizing healthcare globally by enhancing diagnostic accuracy, predicting patient outcomes, and enabling personalized treatment plans. However, in low- and middle-income countries (LMICs) like Pakistan, the integration of AI into healthcare is limited due to challenges such as lack of funding, provider resistance, and inadequate training. Despite these barriers, there is growing interest among healthcare providers in understanding and adopting AI technologies to improve professional efficiency.
View Article and Find Full Text PDFInfect Drug Resist
January 2025
Department of Orthopedics, First Affiliated Hospital, Chongqing Medical University, Chongqing, People's Republic of China.
Background: Early differentiation between spinal tuberculosis (STB) and acute osteoporotic vertebral compression fracture (OVCF) is crucial for determining the appropriate clinical management and treatment pathway, thereby significantly impacting patient outcomes.
Objective: To evaluate the efficacy of deep learning (DL) models using reconstructed sagittal CT images in the differentiation of early STB from acute OVCF, with the aim of enhancing diagnostic precision, reducing reliance on MRI and biopsies, and minimizing the risks of misdiagnosis.
Methods: Data were collected from 373 patients, with 302 patients recruited from a university-affiliated hospital serving as the training and internal validation sets, and an additional 71 patients from another university-affiliated hospital serving as the external validation set.
Front Public Health
January 2025
AstraZeneca SpA, Milano Innovation District (MIND), Milano, Italy.
Background: Software as a Medical Device (SaMD) and mobile health (mHealth) applications have revolutionized the healthcare landscape in the areas of remote patient monitoring (RPM) and digital therapeutics (DTx). These technological advancements offer a range of benefits, from improved patient engagement and real-time monitoring, to evidence-based personalized treatment plans, risk prediction, and enhanced clinical outcomes.
Objective: The systematic literature review aims to provide a comprehensive overview of the status of SaMD and mHealth apps, highlight the promising results, and discuss what is the potential of these technologies for improving health outcomes.
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