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17 articles for “patient privacy”
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Biomedical Monitoring, IoT in Hospital Industry: Focusing on Solidification of Data Security and Privacy of Patients
Abstract: Improving the security of internet of things (IoT) communication and ensuring the safety of intelligent healthcare systems are significant objectives for biomedical microelectromechanical systems (BioMEMS). BioMEMS, which are at the cusp of healthcare and cutting-edge technology, propel the creation of tailored monitoring, therapeutics, and diagnostics. But because of the intricate security and privacy issues that come with IoT connections in smart healthcare ecosystems, a careful analysis is required. Various security …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 26–29 Read article
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Healthcare IT Innovations: Blockchain Technology for Healthcare Data Security and Privacy
Abstract: The healthcare sector has undergone a significant digital transformation, leading to the generation and sharing of vast quantities of sensitive medical data. While this digitization has improved patient care and outcomes, it has also introduced critical challenges related to data security and privacy. The increasing rate of data breaches in healthcare puts patient confidentiality at risk, mainly leading to identity theft, financial fraud, and loss of public trust in healthcare …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Ethical Consideration in the Use of Artificial Intelligence in Medicine and Healthcare
Abstract: Artificial Intelligence (AI) in medicine and healthcare offers tremendous potential for improving patient care, increasing the precision of diagnoses, and increasing operational efficiency. To ensure responsible application, however, the swift uptake of AI technologies also brings up important ethical concerns that need to be addressed. This article explores various ethical challenges in healthcare AI, including concerns about algorithmic bias, data privacy, informed consent, and accountability. Patients must be aware of …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 23–28 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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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Striking A Balance: Ethical Guidelines for A.I. Integration in Mental Health Services
Abstract: Introduction: Artificial Intelligence (AI) integration in mental health services presents opportunities and challenges. This study examines ethical considerations and proposes guidelines for responsible AI implementation in mental healthcare. The rapid advancement of AI technologies has sparked both excitement and concern within the mental health community, necessitating a thorough examination of their potential benefits and risks. By addressing these ethical considerations, this research aims to contribute to the development of a …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 8–15 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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A Literature Review on Internet of Medical Things
Abstract: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment planning, and patient management through data-driven insights and automation. The Internet of Medical Things (IoMT) represents a significant shift in modern healthcare, enabling real-time patient monitoring, data-driven decision-making, and enhanced medical outcomes. This literature review explores the architecture of IoMT, including perception layer, network layer, transport layer and application layer. It also thoroughly explores key challenges like ensuring data security, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Vaccination in the Era of Precision Medicine: Tailoring Immunization Strategies for Individual Risk Profiles
Abstract: The introduction of precision medicine has caused a paradigm change in the vaccine landscape. Conventionally, vaccination programmes have been homogeneous, targeting immunity at the population level without taking into consideration the individual differences in immune response and vulnerability to diseases that can be prevented by vaccination. However, a more individualised approach to immunisation has been made possible by current developments in genetics, immunology, and data analytics. Within the context of …
Published in International Journal of Vaccines · Vol. 1, Issue 2, 2024 · pp. 32–47 Read article
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Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 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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The Contribution of A. I. in Pharmaceutical Software
Abstract: The integration of Artificial Intelligence (AI) in pharmaceutical software has significantly transformed drug development, regulatory processes, and clinical management. AI-powered tools are revolutionizing data analysis, predictive modeling, and decision-making, enhancing the efficiency and accuracy of drug discovery and development. This article explores the multifaceted contributions of AI to pharmaceutical software, including its applications in drug screening, personalized medicine, clinical trial optimization, and regulatory compliance. Additionally, we examine how AI is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
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Design of an Integrated Health Monitoring System on an IoT-Based Framework
Abstract: With the advent of industrialization, health ailments have become a major cause of concern owing to an inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the health sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. An Integrated Health Monitoring System (IHMS) is presented in this paper. This new IoT-based framework integrates wearable …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 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