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265 articles for “AI-based tools”
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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Milk Allergy: Significance, Detection and Management
Abstract: Milk allergy is a significant public health issue, particularly among infants and young children, with prevalence rates between 2 and 6% in early childhood, declining to 0.1–0.5% in adulthood. It is an immune-mediated adverse reaction to milk proteins, primarily involving immunoglobulin E (IgE)-mediated responses. Symptoms range from gastrointestinal distress and respiratory complications to severe anaphylaxis. The etiology of milk allergy involves genetic predisposition, environmental factors, an immature immune system, and …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 14, Issue 1, 2025 · pp. 15–19 Read article
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Visualizing And Forecasting Stocks Using Single Page Application
Abstract: In the fields of finance and economics, stock price forecasting is a vital and crucial subject. The stock market is not governed by any significant rules that may be used to anticipate or estimate the price of a stock. In an effort to forecast the price in the stock market, several techniques are employed, including technical analysis, fundamental analysis, time series analysis, statistical analysis, etc. However, none of these techniques …
Published in Journal of Electronic Design Technology · Vol. 13, Issue 2, 2022 · pp. 23–28 Read article
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Nutrient-Mediated Activation of Cellular Signaling Pathways: Mechanistic Insights into Attenuation of Toxin Induced Inflammation in Food Animals
Abstract: Dietary and environmental toxins remain a persistent challenge in food animal production, where subclinical and clinical inflammation compromises health, productivity, and food safety. Toxin induced inflammation is driven by oxidative stress, mitochondrial dysfunction, and dysregulated immune signaling, resulting in impaired metabolic efficiency and increased disease susceptibility. Recent advances in nutritional science have revealed that nutrients act not only as substrates for growth but also as signaling molecules capable of modulating …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 1–12 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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User Centric Design: A Framework for Transforming Design Studios into Smart Workspaces
Abstract: In contemporary design studios, the integration of smart technologies has become imperative to enhance productivity, collaboration, and creativity among designers. This research paper presents a comprehensive framework for the transformation of conventional design studios into smart workspaces, focusing on user-centric design principles. The concept of User-Centric Design emphasizes its departure from traditional design approaches by placing the user experience at the forefront of the creative process. It highlights the increasing …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 1–13 Read article
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QSAR Modeling Techniques A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Cybersecurity in Web Automation: A Machine Learning Approach to Lightweight Intrusion Detection
Abstract: Launch-Attack is a lightweight and practical threat-detection framework designed specifically for smaller web-automation environments, including setups that rely on tools such as Selenium. Rather than aiming to replace large enterprise-grade security platforms, the framework focuses on offering an accessible option for developers, testers, and researchers who need real-time monitoring without the heavy resource demands of traditional systems. The model relies on machine-learning techniques implemented through Scikit-learn, enabling it to detect …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 34–40 Read article
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Transforming Cancer Care Through AI-Driven Machine Learning: Real-Time Patient Monitoring and Personalized Intervention Strategies
Abstract: Modern healthcare systems are being improved by artificial intelligence (AI) and machine learning (ML), particularly in the treatment of cancer. An AI-driven machine learning system for monitoring cancer patients in real time and offering tailored therapeutic methods is presented in this research. In order to track health issues in real time, the suggested system gathers ongoing health data from wearable sensors and integrates it with patient medical records. This data …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 31–38 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article
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Sustainable Supply Chain Models for Polymer and Composite Manufacturing: A Data-Driven Assessment of Circular Material Flows
Abstract: Polymer and composite manufacturing is faced with growing demands in waste reduction, resource management, and making a shift towards circular economy principles. Although urgent, the adoption of data-driven tools in each step of a supply chain to facilitate efficient cyclic material flows is low. This paper designs and empirically analyzes sustainable supply chain design in polymer and composite production with a focus on digital traceability, closed-loop and material recovery, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 54–71 Read article
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CNN-Based Diagnosis of Skin Cancer from Dermoscopic Images
Abstract: Skin cancer has become one of the diseases widely spread over the globe, with melanoma becoming a severe threat to one’s health. Detection of such diseases at the initial stage saves an individual from drastic damage. Using a Convolutional Neural Network (CNN) for detecting skin cancer through image classification as benign or malignant provides significant support to dermatological practice and reduces dependence solely on subjective visual examination. Dermatologists often face …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 37–42 Read article
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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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A study to assess the knowledge and attitude towards healthy and regular breakfast among undergraduate students of Moradabad, U.P.
Abstract: A research titled “A study to assess knowledge and attitude towards healthy and regular breakfast among undergraduate students of selected colleges of Moradabad, UP, was conducted in partial fulfillment of the requirement of a degree of ‘Bachelors of Science in Nursing at Vivekanand College of Nursing, Moradabad, UP. The present study is an attempt to determine the students’ knowledge towards healthy and regular breakfast, which in turn will help the …
Published in Journal of Nursing Science & Practice · Vol. 11, Issue 1, 2021 · pp. 6–22 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Super Ni 718 Machinability Investigation on Electrical Discharge Machining Using Hybrid Al 7(075+178) Electrode Under Abrasive Assisted Dielectric
Abstract: As aluminum alloy is the lightest metal and has the best mechanical qualities among metal, it has proven to be a perfect choice for strututal industry, particularly in the aerospace sector.7xxx alloys from the Al alloy family are widely used in aviation constructions due to their outstanding processing, welding efficiency, great specific strength & stiffness, and high toughness. The two aluminum alloys that are most frequently used in airplane structures …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1–17 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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Evaluating the Role of Platelet Indices, with a Focus on Immature Platelet Fraction (IPF), in Differentiating Hyper-Destructive and Hypo-Productive Thrombocytopenia: A Study from Ludhiana, Punjab, India
Abstract: Background: Thrombocytopenia, characterized by a reduction in platelet count, is commonly observed in clinical settings. Its etiology can be broadly classified into hyper-destructive thrombocytopenia, where platelets are destroyed at an accelerated rate, and hypo-productive thrombocytopenia, where platelet production is impaired. Differentiating between these two causes is essential for effective management. The Immature Platelet Fraction (IPF) has emerged as a promising non-invasive diagnostic tool to distinguish these causes. Objectives: The primary …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Multi Response Optimization in Friction Stir Welding Al 7075/SiC/10% Metal Matrix
Abstract: The aim of this investigation is to determine the effect of Friction Stir Welding process parameters such as tool rotational speed, weld speed, tilt angle and tool geometry on Al7075/10%wt./SiC Metal matrix Composite. Composites were prepared by the mechanical stir casting process. L27 orthogonal array was chosen for the experimental design. The response characteristics as tensile strength (UTS ) and hardness (VHN) were measured and optimized with Taguchi based grey …
Published in Journal of Automobile Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 30–38 Read article