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194 articles for “Healthcare Data Integration”
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E-Skin: A Revolutionized Technology
Abstract: E-skin is not just a futuristic concept; it is a rapidly maturing technology with the potential to revolutionize how we interact with the world around us. While challenges remain, the advancements in materials science and sensor technology are paving the way for a future where e-skin is an integral part of our daily lives. From enhancing healthcare and empowering robots to transforming consumer electronics and virtual reality, e-skin holds the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 01–11 Read article
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Role of Blockchain Technology in Health Record Management
Abstract: Maintaining thorough medical records is essential to raising a healthy population in the fast-paced world of global development. Intimidating data breaches have been the consequence of the traditional centralized strategy to maintaining health records, yet it has proven vulnerable. The 2017 Ponemon Cost of Data Breach Study estimated that each compromised healthcare record could incur a significant cost of approximately $380. Regrettably, the 2016 Breach Barometer Report revealed that case …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 1, 2024 · pp. 29–35 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Ethical Considerations in AI-Driven Rehabilitation Robotics: Balancing Innovation and Responsibility
Abstract: Artificial intelligence (AI) is transforming robotics rehabilitation by introducing advanced capabilities such as adaptive therapy, real-time feedback, and personalized assistance, significantly improving outcomes for individuals with neurological and physical impairments. These AI-powered systems offer high levels of precision and consistency in therapy delivery, making them especially beneficial in pediatric and adult rehabilitation settings where engagement and tailored interventions are crucial. However, the integration of AI in healthcare also presents critical …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 24–29 Read article
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Securing Healthcare 5.0: A Review of Applications, Security Challenges, and Future Perspectives
Abstract: Healthcare 5.0 represents a revolutionary shift in the healthcare sector, focusing on individualized, patient-centric care through the integration of different cutting-edge technologies such as internet of things, artificial intelligence, big data analytics, blockchain, and cloud computing to enable healthcare services such as real-time health monitoring, personalized treatments, and access to expert advice regardless of geographic barriers. Potentially, Healthcare 5.0 supports more engaged and effective care and help through a focus …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 22–36 Read article
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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Blockchain Enabled Security Framework: Smart Healthcare
Abstract: To explores the transformative potential of blockchain technology in managing, securing, and ensuring the integrity of Electronic Health Records (EHRs). EHRs, which store vital patient information such as medical histories, diagnoses, prescriptions, and imaging results, are essential for enhancing healthcare delivery. Conventional centralized Electronic Health Record (EHR) systems encounter issues such as susceptibility to single points of failure, security risks, and constraints in maintaining data integrity. By leveraging blockchain’s inherent …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 11–17 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Intelligent Medical Devices and Robotics in Modern Healthcare: Technological Advancements and Economic Considerations
Abstract: The integration of robots and intelligent medical devices in intensive care units (ICUs) represents a significant advancement in healthcare technology. These systems, including robotic assistants, automated monitoring tools, and AI-powered diagnostic devices, are designed to enhance patient care, streamline workflows, and reduce human error. Robots in the ICU can assist with routine tasks such as medication delivery, patient repositioning, and even basic surgeries, enabling healthcare professionals to focus on critical …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 18–27 Read article
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Ensuring Data Traceability Across Multiple Cloud Environments
Abstract: This study investigates the challenges and solutions for ensuring data traceability across multiple cloud environments. With organizations' increasing reliance on cloud infrastructure, maintaining data traceability is crucial for compliance, data integrity, and secure data management. The diversity of cloud systems, spanning public, private, and hybrid models, introduces complexities in tracking data lineage, access, and movement. This study delves into multi-cloud strategies' technical and operational hurdles, such as varying data formats, …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 08–22 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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IoT-Based Diabetes Management: Advancements and Challenges in Healthcare
Abstract: The integration of the Internet of Things (IoT) into healthcare has revolutionized disease management by enabling real-time monitoring, data analysis, and proactive interventions. This paper explores how IoT applications can significantly enhance diabetes management by providing sustainable and innovative healthcare solutions. Leveraging IoT-enabled devices such as Continuous Glucose Monitoring (CGM) systems, smart wearables, and remote patient monitoring tools, diabetes care can be personalized and made more efficient, reducing long-term complications. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article