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12 articles for “Clinical Decision Support”
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The Role of Artificial Intelligence in ICU Patient Monitoring and Predictive Analytics: A Prospective Cohort Study
Abstract: Background: Intensive Care Units (ICUs) face challenges in effectively monitoring critically ill patients. Traditional monitoring methods may not detect subtle signs of deterioration in time, leading to worsened outcomes. Artificial Intelligence (AI)-driven monitoring systems have emerged as a potential solution, promising improved predictive capabilities and patient outcomes. Objective: This study aimed to evaluate the impact of AI-based monitoring systems on ICU patient outcomes, focusing on mortality rates, length of ICU …
Published in International Journal of Nursing Critical Care · Vol. 11, Issue 1, 2025 Read article
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AI-Enabled IV Infusion Monitoring Device for Real-Time Nursing Care Optimization
Abstract: Intravenous (IV) infusion therapy is an essential component of modern healthcare, widely used for administering fluids, medications, and nutrients in clinical settings. However, traditional infusion monitoring methods rely heavily on manual observation by nursing staff, which increases the risk of human error, delayed interventions, and excessive workload. The integration of Artificial Intelligence (AI) into IV infusion systems has introduced a transformative approach to real-time monitoring, predictive analytics, and automated alert …
Published in International Journal of Nursing Critical Care · Vol. 12, Issue 1, 2026 · pp. 10–18 Read article
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SYNTHETIC MEDICAL DATA GENERATIONUSING GAN MODEL
Abstract: The healthcare industry has witnessed growing interest in synthetic data generation, driven by increasing demands for large and diverse datasets. Real medical data is often inaccessible due to stringent privacy laws, data scarcity, and ethical considerations. Sophisticated models, such as Generative Adversarial Networks (GANs), have emerged as powerful tools to generate synthetic data that closely resembles real-world data. This approach is particularly effective for addressing the challenges of researching rare …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 2, 2025 Read article
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Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
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Enhancing Glaucoma Detection with Convolutional Neural Networks: A Data-Driven Approach
Abstract: One of the main causes of irreversible blindness is glaucoma, which is characterized by certain alterations in the optic nerve that over time can impair vision. Manual evaluations, while invaluable, are challenged by inconsistencies, subjectivity, and the extensive time required. The study employed a dataset comprising retinal images annotated by experts. By using Convolutional Neural Networks (CNNs) to study and recognize important patterns in eye images, it was possible to …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 11, Issue 1, 2025 · pp. 1–6 Read article
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Closing Gaps in Asthma Care: Role of Nurse in Addressing Challenges, Barriers and Opportunities in Universal health coverage
Abstract: Background: Chronic respiratory illness is increasing and are a health burden in India, there are nearly 37 million asthmatics around the world. India contributes to 11.1 per cent of the global asthma burden and accounts for over 42 per cent of related deaths making it the asthma capital of the world. According to The Global asthma report (2018), the barriers to implementing successful treatment methods for Asthma in India is …
Published in International journal of Nursing Science Practice and Research · Vol. 9, Issue 1, 2023 · pp. 34–38 Read article
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Smart Hospital Bed System for the Prevention and Management of Bedsores and Pressure Ulcers
Abstract: Pressure ulcers, also known as bed sores, represent a critical challenge in modern healthcare, particularly among immobilized and critically ill patients, leading to increased morbidity, prolonged hospital stays, and higher healthcare costs. Recent advancements in smart healthcare technologies have enabled the development of smart hospital bed systems that integrate sensors, automation, and artificial intelligence to prevent and manage pressure ulcers effectively. These systems incorporate features such as pressure redistribution, automatic …
Published in International Journal of Nursing Critical Care · Vol. 12, Issue 1, 2026 · pp. 1–8 Read article
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The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment
Abstract: Artificial intelligence (AI) is increasingly reshaping mental health care by supporting early identification of mental health conditions, improving diagnostic accuracy, and enabling personalized intervention strategies for disorders such as depression, anxiety, and post-traumatic stress disorder. Advanced AI technologies, including machine learning algorithms and natural language processing techniques, allow analysis of large-scale behavioral, textual, and speech-based data to identify patterns related to emotional and cognitive health. These tools help clinicians make …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 22–26 Read article
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The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment
Abstract: Artificial intelligence (AI) is increasingly reshaping mental health care by supporting early identification of mental health conditions, improving diagnostic accuracy, and enabling personalized intervention strategies for disorders such as depression, anxiety, and post-traumatic stress disorder. Advanced AI technologies, including machine learning algorithms and natural language processing techniques, allow analysis of large-scale behavioral, textual, and speech-based data to identify patterns related to emotional and cognitive health. These tools help clinicians make …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 Read article
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Comprehensive Assessment and Instructional Methods for Nursing Professionalism
Abstract: Professionalism among healthcare workers forms the cornerstone of safe, effective, and ethical healthcare delivery. It places the well-being and interests of the patient or client at the core, aligning with public expectations and ensuring it remains central to all clinical decisions and actions. As a dynamic and evolving concept, professionalism is based on key professional values, including respect for oneself and others, compassion, self-awareness, honesty, integrity, accountability, and a dedication …
Published in International journal of Nursing Science Practice and Research · Vol. 11, Issue 2, 2025 · pp. 13–18 Read article
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Artificial Intelligence in Nursing: Empowering the Workforce of Tomorrow
Abstract: Artificial Intelligence (AI) is transforming modern healthcare, including nursing practice, by enhancing clinical decision-making, improving patient outcomes, and simplifying administrative tasks. The article also explains the benefits of AI in nursing, such as increased diagnostic accuracy, better time management, and easily accessible mental healthcare for nurses. However, there are drawbacks to using AI, including algorithmic bias, data privacy, moral dilemmas, and the possibility of care disassociation, all which are properly …
Published in International journal of Nursing Science Practice and Research · Vol. 12, Issue 1, 2026 · pp. 6–11 Read article
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The Future of Nursing Education: Harnessing the Power of Objective Structured Clinical Examinations (OSCEs)
Abstract: Objective Structured Clinical Examination (OSCE) is a structured and systematic assessment method widely used to evaluate clinical skills, knowledge, communication, decision-making, and professional competencies among nursing students. Effective implementation of OSCEs requires nursing faculty to possess adequate knowledge, confidence, and practical skills related to examination planning, station development, administration, and evaluation. This study aimed to develop a comprehensive handbook on OSCEs and assess its impact on the knowledge, attitude, and …
Published in International journal of Nursing Science Practice and Research · Vol. 12, Issue 2, 2026 · pp. 12–16 Read article