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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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Role of Application of SWCR Guidelines in Management of Right Trochanter Pressure Injury (PI)
Abstract: A pressure injury refers to the localized death of tissue resulting from sustained pressure on the skin and underlying tissues. This damage is often compounded by shear forces or direct trauma to the skin. While terms like “decubitus ulcer,” “bedsore,” and “pressure sore” are commonly used interchangeably, they fail to capture the complexity of the condition as accurately as the term “pressure injury” does. The term “decubitus” originates from Latin, …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 2, 2024 · pp. 30–40 Read article
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Crime Prediction and Criminal Identification System Using Machine Learning
Abstract: Advanced machine learning and data analytics-driven crime prediction and criminal identification systems have become game-changing instruments for contemporary law enforcement. Utilizing past crime statistics, surveillance footage, and additional resources, these systems forecast criminal activity, manage resources efficiently, and improve investigation capacities. With an emphasis on their importance in enhancing public safety and lowering crime rates, this paper presents an overview of criminal identification and prediction systems. Examining the technologies and …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Counter Terrorism Prediction and Risk Evaluation (C-TRIP)
Abstract: The global landscape in the 21st century is marked by complex and evolving security challenges, none more pressing than the threat of terrorism. Acts of terror have left a profound impact on societies, economies, and governments worldwide, underscoring the critical importance of effective counter terrorism strategies. The “Counter Terrorism Prediction and Risk Evaluation (C-TRIP)” represents a significant stride in addressing this ever-pressing challenge. In a time marked by global security …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 14–24 Read article
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The Transformative Journey of Pregnancy: Insights into Maternal Adaptations
Abstract: During pregnancy, a woman’s body changes in many ways because of hormones. These changes can sometimes be uncomfortable, but most of the time they are normal and enable her to nourish and protect the fetus, prepare her body for labor, and develop her breasts to produce milk. During pregnancy, changes in hormone levels drive a wide range of physical transformations in a woman’s body, all of which play an essential …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 84–92 Read article
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Climate Change Including Forest Fire Prediction using Machine Learning and Deep Learning
Abstract: Climate change alludes to long haul shifts in temperatures and atmospheric conditions. These movements might be regular, for example, through varieties in the sun-oriented cycle. In any case, since the 1800s, human exercises have been the fundamental driver of climate change, basically because of consuming fossil fuels like coal, oil and gas. Many individuals think climate change mostly implies hotter temperatures. Be that as it may, the temperature climb is …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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Experimental Analysis of Axially Compressed Precast Concrete Pressure Pipes Filled with Concrete
Abstract: Humanity has always been at the mercy of natural disasters, which frequently result in widespread devastation and displacement. However, scientific advancements, technological innovations, and extensive research have significantly mitigated the loss of life, property, and essential resources. One of the critical challenges in the aftermath of disasters is providing adequate and timely shelter, food, and medicine to the affected populations, often under constrained resources and logistical difficulties. In response to …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 28–37 Read article
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Prescription Opioid Use, Misuse and Motivation for Misuse among patients admitted in a drug treatment center
Abstract: Background: Opioid misuse remains a significant public health concern in Nigeria and globally. The risk of misuse complicates opioid prescriptions, potentially leading to overdose and fatal outcomes if not promptly addressed. Objectives: To determine the prevalence of prescription opioid use, misuse, and the underlying motivations for misuse. Method: This study utilized a retrospective cross-sectional design to examine the prevalence and patterns of prescription opioid use and misuse. Data were collected …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 2, 2025 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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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 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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Role of Food Supplements in Premalignant Lesions: A Literature Review
Abstract: Premalignant lesions of the oral cavity are histopathological alterations in the oral epithelium linked to a higher likelihood of malignant transformation. These lesions frequently present as leukoplakia (white patches), erythroplakia (red patches), oral lichen planus, and oral submucous fibrosis. Oral cancer, categorized among head and neck malignancies, is considered the sixth most common cancer globally. While tobacco and alcohol consumption remain the primary etiological factors, increasing evidence underscores the significant …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 17–26 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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SmartMed: An AI Powered Platform for Instant Medicine Access and Prescription Understanding
Abstract: Access to medicines during emergencies and the lack of prescription clarity remain significant challenges in modern healthcare systems. Most existing online pharmacy platforms primarily focus on home delivery services and do not provide real-time visibility of nearby pharmacy stock or intelligent prescription interpretation support. This limitation often delays treatment and creates confusion for patients. This paper presents a Smart Medicine Availability, Delivery, and AI Consultation System that integrates real-time pharmacy …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 1–15 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article