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360 articles for “prediction tool”
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Digital Tympanic Membrane Temperature versus Digital Axillary Temperature: Comparative Study among Neonates
Abstract: Neonatal hypothermia continues to be a significant issue in the developing countries and there remains considerable controversy regarding the most appropriate thermometer and the best anatomical site for temperature measurement. In this diagnostic study, the prime objective was to find which thermometry practice could be proved effective for assessment of temperature in neonates. For this, the authors evaluated the agreement between tympanic thermometry measurements, digital axillary thermometry measurements and skin …
Published in Journal of Nursing Science & Practice · Vol. 4, Issue 1, 2014 · pp. 38–46 Read article
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Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems
Abstract: In this paper, a detailed analysis of dielectric breakdown and electrical aging behavior of high-voltage insulating polymer material has been proposed through sophisticated MATLAB simulation. The research involves electric field modeling, aging life prediction, partial discharge (PD) behavior and uncertainty modeling using Monte Carlo analysis. Electric field hotspots causing critical behavior, sensitivity of the lifespan to electric stress, and the stochastic PD build-up allow predictive diagnostics of the health of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 173–187 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
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Finite Element, Experimental, and Machine Learning-Based Optimization of Machining Stability for Polymer Composite Material Processing
Abstract: The machining of polymer composite materials, particularly fibre-reinforced polymer-matrix composites, requires stable spindle-tool performance to avoid delamination, fibre pull-out, matrix cracking, thermal softening, poor surface integrity, and premature tool wear. In line with the scope of the Journal of Polymer & Composites, this study presents an integrated finite element, experimental, and machine learning framework for improving machining stability during end-milling of composite material systems. The spindle-tool assembly is modelled using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Adoption of Artificial Intelligence in Periodontal Diagnostics: Awareness, Confidence, and Barriers Among Dental Practitioners in India
Abstract: AI has emerged as a transformative tool in healthcare, including periodontics, where it aids in diagnosing periodontal diseases, assessing bone loss, and predicting disease progression. Despite its potential, the adoption of AI in dentistry, particularly in India, remains limited. This study aimed to evaluate the awareness, confidence, and willingness of dental practitioners to adopt AI-based tools in periodontal diagnostics. A cross-sectional survey was conducted among 106 dental practitioners, including general …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 27–38 Read article
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Next Generation Sequencing (NGS) in Personalized Medicine: Emphasizing Public Health Beyond Reality
Abstract: NGS is a modern technology that allows researchers to quickly sequence large amounts of DNA or RNA, it is also known as massively parallel sequencing or deep sequencing. NGS has revolutionized genomic research and biological sciences by its speed, scale, accuracy, ultra-high throughput, and cost. NGS replaced the conventional sequencing method. A novel idea in healthcare is precision medicine, which involves adjusting medical care to each patient’s unique traits and …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 · pp. 1–17 Read article
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Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Analysis of Die Corner Gap Formation for Strain Hardening Materials in ECAP Through an Upper Bound Sensitivity Approach: A Comparative Study
Abstract: In recent work, using a proposed central composite factorial analysis, the upper-bound theorem's theoretical concept for the equal channel angular pressing process are used. The upper-bound theorem-based theoretical solutions consider Tresca friction conditions and varied fillet radii at the die channel junction. When using AA5083's uniaxial mechanical properties, isotropic nonlinear work hardening is assumed. The ratio of the cumulative effective plastic strain to the time generated by the deformation zones, …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 1–22 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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A Review on Transforming Patient Pathways: The Impact of Pharmaceutical Software on Drug Manufacturing and Safety Monitoring
Abstract: The development, production, and safety monitoring of pharmaceuticals are being revolutionized by incorporating digital technologies. Throughout drug lifecycles, pharmaceutical software which includes cloud-based systems, automation, data analytics, and artificial intelligence (AI) has emerged behind efficiency and innovation. Real-time monitoring, predictive maintenance, and process optimization are made possible in manufacturing by software tools like Digital Twins, Manufacturing Execution Systems (MES), and Quality Management Systems (QMS). These technologies improve batch consistency, lower …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 40–46 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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Performance test to determine electric vehicle driving range
Abstract: A new method to estimate the driving range in electric vehicles has been developed. The new method is based on full electric energy supply from a unique lithium-ion battery that equips the electric vehicle. The simulation method includes engine consumption as well as auxiliary systems and accessories that are currently powered by a servicing lead-acid battery. The modeling uses an AC/DC double electric circuit to represent the AC electric engine …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 2, 2021 · pp. 10–20 Read article
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Rainfall Runoff Modeling Using SCS-CN Method: A GIS Based Case Study of Pawana Watershed
Abstract: In a country over 125 million, we are proudly an agricultural based economy, wherein 51% of population is indulged in any business related to somehow with agriculture. Of course, we still are in a developing stage as far as methodologies or their implementation is concerned. But surely somewhere we have started focusing on modern techniques and strategies to improve pattern, productivity, profit and all. The two vital natural resources required …
Published in Journal of Water Resource Engineering and Management · Vol. 3, Issue 3, 2016 · pp. 50–58 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article