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1940 articles for “pre” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Effectiveness of a Structured Educational Intervention on Managing Minor Disorders of Pregnancy Through Home Remedies Among Antenatal Women in Urban and Rural Kuppam
Abstract: Pregnancy is a physiological process often accompanied by minor disorders such as nausea, vomiting, backache, heartburn, and fatigue, which can affect the well-being of expectant mothers. Appropriate knowledge and timely management using simple home remedies can significantly reduce discomfort and improve maternal health. This study aimed to evaluate the effectiveness of a structured educational intervention on the management of minor disorders of pregnancy through home remedies among antenatal women in …
Published in International Journal of Midwifery Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 7–15 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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Understanding the Level of Knowledge and Attitudes of Pregnant Women on Use of Complementary and Alternative Medicine (CAM)
Abstract: Background: The utilization of complementary and alternative medicine (CAM) among pregnant women in India is on the rise. Though the pregnant women are using these therapies, they lack adequate knowledge. It is the responsibility of the health care provider to identify the knowledge to promote healthy practices and to avoid harmful practices. Method: For this investigation, a quantitative method was used. The level of knowledge and attitude of pregnant women …
Published in International Journal of Midwifery Nursing And Practices · Vol. 1, Issue 1, 2023 · pp. 25–30 Read article
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A Study to Assess the Prevalence of Tokophobia and the Effect of Nurse-led Intervention on Birth Experience Among Parturients Availing Services in a Tertiary Care Hospital, Kolkata
Abstract: Introduction: Tokophobia, the fear of childbirth, can significantly impact a woman's birth experience and overall well-being. This study aims to determine the prevalence of tokophobia among parturients and evaluate the effectiveness of a nurse-led intervention in improving birth experiences in a tertiary care hospital in Kolkata. Methods: A cross-sectional study design was employed to assess the prevalence of tokophobia among parturients receiving services at the selected tertiary care hospital in …
Published in International Journal of Midwifery Nursing And Practices · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Safe Travel: Road Accident Analysis, Severity Prediction, and Safe Route Mapping
Abstract: Road accidents pose a significant threat to public health, resulting in millions of injuries and fatalities annually. With an estimated 1.2 million lives lost and 20 to 50 million people injured each year, the escalating trend of traffic accidents demands urgent attention. To address this issue, specialists utilize advanced algorithms such as random forests to analyze historical road crash data, aiming to predict accident hotspots. By identifying patterns and trends …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 39–44 Read article
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A Quasi-Experimental Investigation of The Effects of Two Different Negative Pressure Levels During Open Endotracheal Tube Suctioning on Physiological Parameters in Mechanically Ventilated Patients in The PCCM ICU At Pt. B.D. Sharma P.G.I.M.S., Rohtak
Abstract: Introduction: Patients who are intubated often have difficulty clearing secretions through coughing. As a result, endotracheal suctioning is essential to minimize the risk of consolidation and atelectasis, which could impair ventilation. However, suctioning can pose several risks and complications, including bleeding, infection, atelectasis, hypoxemia, cardiovascular instability, increased intracranial pressure, and potential damage to the tracheal mucosa. The level of negative pressure applied during suctioning plays a crucial role in the …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 2, Issue 2, 2024 · pp. 29–58 Read article
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Assessing the Impact of a Structured Educational Initiative on Awareness of Vaginitis and Its Prevention Among Adolescent Girls in Selected Higher Secondary Schools in Bengaluru
Abstract: Background and Objectives: Vaginal inflammation, referred to as vaginitis, may culminate in discharge, itching, and pain. Usually, the root cause is an infection or an altered in the balance of the microbes in the vagina. In females between the ages of two and six, poor perineal hygiene—such as wiping after bowel movements from back to front or not washing hands afterward—is an important contributory factor. Another typical sign is frequent …
Published in International Journal of Midwifery Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 10–21 Read article
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Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level
Abstract: Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 1–24 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
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Precision Medicine Approaches for Cancer Therapy Recent and Advance
Abstract: Recent advances in biotechnology have made it possible to identify intricate and distinctive biological characteristics linked to carcinogenesis. Proteomic and RNA studies, immunological markers, tumor and cell-free DNA profiling, and other methods are utilized to find these traits in order to optimize anticancer treatment for specific patients. In recent years, the focus of clinical trials has shifted considerably to enhance treatment outcomes in cancer therapy. Rather than being primarily centered …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 1–11 Read article
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A Single Case Study on Ayurvedic Therapeutic Management for Increasing Growth Hormone in Pre-Pubertal Girl
Abstract: Human growth hormone, commonly referred to as HGH and somatotropin, is a naturally occurring hormone released by the pituitary gland that promotes growth in children by acting on various body regions. The pituitary gland produces the polypeptide hormone known as human growth hormone (hGH), or somatotropin, which is made up of 191 amino acids. A lack of human growth hormone (hGH) in children can result in growth failure, low stature …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 1, 2025 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Caries-Preventive Effects of Self-Applied Subacidic 0.5% NaF-HF Gel via Toothbrushing in 7–8-Year-Old Schoolchildren: A Randomized Controlled Clinical Trial
Abstract: To assess the caries-preventive effectiveness of self-applied subacidic 0.5% sodium fluoride–hydrofluoric acid (NaF-HF) gel used during toothbrushing in children aged 7–8 years Objective: To assess the caries-preventive effectiveness of self-applied subacidic 0.5% sodium fluoride–hydrofluoric acid (NaF-HF) gel used during toothbrushing in children aged 7–8 years. Methods: This 1-year, multi-arm, double-blind, placebo-controlled, parallel-group randomized study evaluated the caries-preventive efficacy of self-applied 0.5% NaF-HF gel among primary schoolchildren. A total of 1200 …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 1, 2026 · pp. 14–19 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article