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88 articles for “recurrence”
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Navigating the Principles and Practice of Oral Anticoagulant Therapy: A Comprehensive Healthcare Guide
Abstract: Oral anticoagulant therapy plays a critical role in the prevention and treatment of thromboembolic disorders, including atrial fibrillation (AF), venous thromboembolism (VTE), and mechanical heart valve replacement. This research article aims to provide a comprehensive overview of the principles and practice of oral anticoagulant therapy, focusing on the mechanisms of action, pharmacokinetics, clinical indications, monitoring, and management of associated complications. The cornerstone of oral anticoagulant therapy includes vitamin K antagonists …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 76–82 Read article
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Erythrodermic Psoriasis: A Case Report Highlighting Clinical Features and Management
Abstract: Background: Erythrodermic psoriasis (EP) is a rare and severe variant of psoriasis that presents as widespread erythema, scaling, and systemic complications such as fever, dehydration, and electrolyte imbalances. It requires urgent medical attention due to the risk of life-threatening complications, including sepsis and multi-organ failure. The condition can arise de novo or as an exacerbation of pre-existing psoriasis, often triggered by medication withdrawal, infections, or systemic inflammation. Case Presentation: We …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 01–05 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Therapeutic Potential of Terminalia arjuna Bark in the Management of Hemorrhoids: A Comprehensive Review
Abstract: Background: Hemorrhoids appear frequently among anorectal disorders since they create vascular swelling together with pain symptoms, while leading to bleeding and mucosal tissue tending to slide out. Though effective therapy exists, traditional treatments produce various adverse effects and lead to recurrence and inconsistent patient following of medical recommendations over the long term. Plantbased therapeutic medicines have gained rising demand, which leads experts to investigate medicinal plants with established pharmacological effects. …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 2, 2025 · pp. 22–32 Read article
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Neuro-Rehabilitation Reimagined: A Cross-Cultural Paradigm Integrating Immunotherapeutics and Multidimensional Analytics in Pediatric Cerebral Palsy
Abstract: Researchers performed multidimensional data analysis on the clinical records of 1,586 cerebral palsy pediatric patients to investigate the rehabilitative benefits of immunotherapy and the advantages of blending Traditional Chinese Medicine with Western treatments. A multi-center, prospective cohort study established a standardized system for data gathering that included clinical baseline databases along with treatment protocols and follow-up information. Baseline data analysis showed substantial patient diversity across clinical types and TCM syndromes …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 67–84 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Role of Artificial Intelligence in Health Care Decision Making: Balancing Innovation and Caution
Abstract: Healthcare is undergoing a transformation powered by artificial intelligence, which improves monitoring, diagnosis, and treatment capabilities. Among Artificial Intelligence (AI's) shortcomings is the dearth of an emotional relationship between individuals and medical personnel. Robotic surgery procedures pose the possibility of malfunctioning machinery and mistaken assumptions. So, the present systematic review focused on exploring the boon and bane of the role of AI in predicting various abnormalities in advance to improve …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 24–35 Read article
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Comprehensive Review on Antimicrobial based Hydrogel for Wound Healing
Abstract: Chronic wounds present a significant clinical challenge due to their prolonged healing time, high risk of infection, and frequent recurrence. The development of novel wound dressings with both healing and antimicrobial properties is essential for effective wound management. This study focuses on the formulation and evaluation of an antimicrobial drug-loaded hydrogel designed to promote chronic wound healing. Chronic wounds are a growing concern in healthcare, often taking weeks or even …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 2, 2025 · pp. 72–88 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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A Thorough Analysis of Herbal and Synthetic Methods for Treating Peptic Ulcers
Abstract: Many people are afflicted with ulcers, a common gastrointestinal disorder. In essence, they are inflammatory lesions that form in the digestive tract's skin or mucous membrane lining. An imbalance between preventive and damaging factors—either from reduced mucosal defences or from increased aggressive elements—leads to ulcer development. Their development is influenced by a number of variables, including as stress, poor eating habits, and long-term pharmaceutical use. The word "peptic ulcers" refers …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 2, 2025 · pp. 55–71 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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A Systematic Review on Peptic Ulcer Disease and its Pharmacological Treatment
Abstract: A chronic gastrointestinal condition known as Peptic Ulcer Disease (PUD) is typified by the formation of ulcers or mucosal erosions in the proximal duodenum and stomach. In the pathophysiology of PUD, the equilibrium between defensive processes like mucus and bicarbonate secretion, mucosal blood flow, and prostaglandin production, and aggressive factors such stomach acid secretion, pepsin activity, and Helicobacter pylori infection, is upset. Although stress and food have historically been blamed, …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 76–84 Read article
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Studies of Mathematics: A Review of Research Trends, Themes and Implications
Abstract: This review examines contemporary research trends, thematic developments, and emerging implications within the field of mathematics education and mathematical studies. Drawing on a synthesis of recent scholarly literature, it explores how mathematics as both a discipline and a pedagogical practice continues to evolve in response to technological advancements, interdisciplinary applications, and changing educational paradigms. Major research trends reveal a growing emphasis on problem-based learning, mathematical modeling, and the integration of …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 19–24 Read article
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Immune Dysregulation and Cytokine Circuitry in Genital Endometriosis: Mechanistic Insights and Next-Generation Immunotherapeutic Strategies
Abstract: Genital endometriosis is increasingly recognized as an immune-mediated inflammatory disorder driven by complex interactions between dysregulated immune cells, cytokine hubs, and microbiome-derived modulators. This review introduces a novel “immune–cytokine circuitry” framework that unifies innate and adaptive immune abnormalities with key cytokine loops sustaining chronic inflammation, angiogenesis, neuroinflammation, and immune tolerance. Within this circuitry, macrophage polarization, dendritic cell immaturity, NK-cell anergy, Treg expansion, Th17 amplification, and B-cell–mediated autoimmunity converge to establish …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 06–16 Read article
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Integrating Plant Selection, Planting Design, and Landscape Construction for Sustainable Site Development
Abstract: This paper explores the interrelationship between plant selection, planting design, and landscape construction in achieving ecologically sustainable and aesthetically pleasing outdoor environments. Plant selection involves choosing species that are well adapted to site conditions, ecological functions, maintenance regimes, and visual preferences. Planting design refers to the arrangement, composition, and spatial organization of plant materials to meet functional, aesthetic, and environmental objectives. Landscape construction encompasses implementation—from site preparation and planting through …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article
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Hardware Solution for LVRT Enhancement Techniques in DFIG - A Review
Abstract: With the advancement of wind power technology, penetration of wind power to power systems has increased significantly. Grid codes require that the wind generators should remain connected for specified time even under low voltage conditions. Stricter grid code requirements are now necessary to assure system stability and reliability due to the growing integration of wind power into contemporary power networks, which is being pushed by the quick development of wind …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 59–73 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article