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817 articles for “Classify”
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
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Evaluating Andrographis paniculata Phytochemicals as Potential Glioma Therapeutics via Molecular Docking Approach
Abstract: Evaluating Andrographis paniculata Phytochemicals as Potential Glioma Therapeutics via Molecular Docking ApproachGlioneuronal tumors and gliomas are grade I tumors classified by the World Health Organization (WHO). They typically grow slowly and primarily affect infants, children, and teenagers, but can also occur in adults. They mostly cause seizures caused by gangliomas. Most current treatments include surgery and radiotherapy. Since this disease affects children, the current treatments may cause complications. Andrographis paniculata …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 82–93 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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Extra Philadelphia in CML Due to Isodicentric 22: A Case Report
Abstract: Introduction: Chronic Myelogenous Leukemia is a malignancy that affects the hematopoietic stems cells (HSC) of the bone marrow, leading to the rapid and continual proliferation of granulocytes and precursor blast cells. This is caused due to a reciprocal translocation that occurs between chromosomes 9 and 22, leading to the formation of derivative 22 also called as Philadelphia (Ph) chromosome. The Ph chromosome then encodes a fusion oncoprotein that functions as …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 18–22 Read article
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Comparision Of Success Rate Of Ultrasound-Guided Versus Landmark Technique For Caudal Block In Children
Abstract: Background: Caudal block is one of the most widely used epidural techniques in children, and this study compares its success when performed using ultrasound guidance versus the traditional landmark method. Methods: Forty-six children aged seven years or younger, classified as ASA I–II and undergoing surgery under general anesthesia with caudal analgesia, were enrolled and randomly assigned to either the landmark group (Group C, n = 23) or the ultrasound group …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Self Healing Material: An Introduction
Abstract: Self-healing materials have emerged as a transformative innovation for sustainable infrastructure and advanced applications such as wearable electronics and smart transportation systems. These materials possess the intrinsic ability to repair damage autonomously or with minimal external intervention, thereby extending service life and reducing maintenance costs. Inspired by biological systems, self-healing mechanisms are broadly classified into extrinsic approaches, such as microcapsule and vascular networks based healing, and intrinsic mechanisms involving reversible …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 604–611 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Characteristics of Group VIII Elements in the Periodic Table and the Potential Uses and Applications
Abstract: Group 8 elements, known as noble gases, hold a special place in the periodic table. Noble gases offer unique properties with applications in science, industry, and technology. By comprehensively understanding the characteristics of Group 8 elements, we not only appreciate their role in the periodic table but also recognize their significance in scientific research and industrial applications. This project sheds light on the unique properties of noble gases, highlighting their …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 82–91 Read article
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An Integrative Review of Male Sexual Disorders and the Therapeutic Role of Unani Aphrodisiacs
Abstract: Sexual health is a vital component of overall well-being, encompassing physical, emotional, and psychosocial dimensions. Male sexual dysfunction – including conditions, like erectile dysfunction, premature ejaculation, and low libido – can significantly impact quality of life and intimate relationships. Aphrodisiacs, derived from the Greek goddess Aphrodite, are substances that stimulate sexual desire and performance. Historically, natural aphrodisiacs have been used in various cultures and include plant-based substances such as Yohimbine, …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Cosmeceuticals: Integrating Therapeutic Functionality into Cosmetic Science
Abstract: Cosmeceuticals are a quickly growing group of skincare products that are in between cosmetics and drugs. These products have biologically active components that are said to provide medical or drug-like advantages for a number of skin problems, including ageing, hyperpigmentation, acne, and damage from the sun. Cosmetics are not medications, but cosmeceuticals are made to affect skin function at the cellular level. This article talks about what cosmeceuticals are, how …
Published in Recent Trends in Cosmetics · Vol. 2, Issue 2, 2025 · pp. 19–35 Read article
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ECO Report Analys Achieving SDG 15
Abstract: This project creates automated data processing tool Eco Data Analyser for ecological data analysis for SDG 15: Life on Land conservation and biodiversity. File_picker, Excel, and CSV are used in the Flutter and Dart based cross-platform solution to assist environmental organizations in handling ecological data. Uploading ecological datasets, verifying data, classifying biodiversity indicators, and producing summary reports helps Eco Data Analyser to make conservation data accessible and valuable. User-defined parameters …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Natural Language Processing in Everyday Applications: From Classrooms to Clinics
Abstract: Natural Language Processing (NLP) is transforming everyday sectors like healthcare and education by creating new opportunities for efficiency, accessibility, and early intervention. This paper investigates the function of natural language processing (NLP) in computer education. Tools like automated grading systems, intelligent tutoring assistants, and multilingual translation platforms are revolutionizing traditional teaching methods. Despite its benefits, adoption is still being slowed down by problems like data privacy, integration with education, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article
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A Comparative Study to Assess the Fetal Outcome Among Normal and Anemic Mothers at Sultania Zanana Hospital at Bhopal
Abstract: Anemia during pregnancy is a significant public health concern, especially in developing countries like India. It is a clinical condition characterized by a deficiency in hemoglobin levels, often due to inadequate intake of essential nutrients such as iron, folic acid, and vitamins. The World Health Organization classifies anemia during pregnancy as having hemoglobin levels under 11 g/dL, with specific thresholds varying by trimester. Maternal anemia not only affects the mother's …
Published in International Journal of Midwifery Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 41–74 Read article