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26 articles for “healthcare workflows”
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Pharma Guard: Smart Medication Management System
Abstract: Pharma Guard Smart Medication Management System presenting a comprehensive overview of an innovative technology designed to revolutionize medication management in healthcare settings. In an era of advancing digital solutions, the Pharma Guard system offers a sophisticated approach to ensuring medication safety and adherence. Through the integration of smart technology, including internet of things (IoT) devices and machine learning algorithms, Pharma Guard enables real-time monitoring, tracking, and management of medication consumption …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 1, 2024 · pp. 30–37 Read article
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Revolutionizing Orthopedic Nursing: The Transformative Impact of Artificial Intelligence on Patient Care and Nursing Practices
Abstract: The use of Artificial Intelligence (AI) in orthopedic nursing care has become a game-changer, significantly improving patient care, surgical results, and the efficiency of nursing processes. This review explores the latest trends in AI applications within the field of orthopedic nursing, detailing the scope of these technologies, their impact on patient care, and the challenges faced by healthcare professionals. By examining contemporary literature, this review aims to provide insight into …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 13–17 Read article
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Clinical and Administrative Processes in Contemporary Dental Practice
Abstract: Maintaining operational efficiency, providing patients with high-quality oral healthcare, and guaranteeing patient pleasure all depend on a dental clinic operating well. This article looks at the administrative procedures, clinical workflow, and organizational structure that go into running a dental clinic on a daily basis. Patient scheduling, infection control procedures, dental equipment management, staff roles and duties, record-keeping, and adherence to legal and ethical standards are some of the important topics …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 1, 2026 · pp. 19–24 Read article
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Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform
Abstract: The rapid progress of the Fourth Industrial Revolution has been largely driven by the evolution of artificial intelligence (AI), with notable contributions from technologies such as Generative Pre-trained Transformers (GPT). This revolution has seen the convergence of physical, digital, and biological technologies, leading to transformative impacts across various sectors. Data science, serving as a crucial enabler, has enabled the development of intelligent value chains. However, the application of data science …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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AI Activity to Enhance Productivity, Creativity, and Sustainable Development of AI in Healthcare
Abstract: The application of artificial intelligence (AI) in healthcare is revolutionizing the industry by fostering both productivity and creative approaches to patient care and medical research. This study explores how artificial intelligence (AI) is reshaping healthcare by streamlining workflows, improving diagnostic precision, and supporting personalized treatment plans. AI-powered technologies are reshaping the way medical professionals approach patient care, providing tools that not only automate routine administrative and clinical tasks but also …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 21–29 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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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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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 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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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Literature Review on Real-Time Dashboard Systems in Healthcare and Education
Abstract: Real-time dashboards are revolutionizing data analysis and visualization within education and healthcare, highlighting the realms of online learning analytics and emergency medicine. Such systems maximize decision-making power, efficiency of workflows, and awareness in real time. The literature review below explores diverse methodologies, benefits, and pitfalls, and presents suggestions for potential avenues for research in the future. Growing access to data and advancements in visualization and analytics technologies have given rise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 01–05 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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Advanced Security Mechanisms for Protecting Mobile Devices: A Comprehensive Analysis of Threats and Counter Measures
Abstract: The digitization of clinical care has led to significant advancements in medical devices and telemetry, fundamentally transforming the healthcare landscape. These innovations have enhanced the quality of patient care by enabling more accurate diagnoses, real-time monitoring, remote consultations, and increased transparency in clinical workflows. As a result, modern medical practices have become more efficient, data-driven, and patient-centric. Devices such as infusion pumps, pacemakers, ventilators, and wearable monitors now rely heavily …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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AI in Healthcare: Drug Delivery in Tuberculosis
Abstract: Tuberculosis (TB) , mainly caused by Mycobacterium tuberculosis, remains a major global health burden, accounting for millions of new infections and deaths each year. Although progress has been made in diagnosis and treatment, the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB makes disease control increasingly difficult. Conventional diagnostic approaches such as chest X-rays, sputum smear microscopy, and culture methods continue to play an important role, but they …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 9–17 Read article
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Glitches in the Implementation of Bioinformatics in Medical Settings: A Comprehensive Review
Abstract: Bioinformatics is a dynamic field at the intersection of biology, computer science, and information technology, offering new possibilities in medicine by enabling a deeper understanding of genomics, molecular biology, and personalized treatment approaches. Its integration into healthcare could greatly enhance diagnostics, enable tailored treatments for individuals, and facilitate the analysis of large biological datasets. However, despite its potential, several barriers impede its successful implementation in clinical settings. These include technical …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article