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310 articles for “early detection”
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A Screening Study on Occurrence and Distribution of Urinary Tract Infections Among Suspected Cases (Pyuria, With or Without Symptoms) During Pregnancy
Abstract: Background: Urinary tract infection is one of the most frequently seen medical complications in pregnancy. Methods: Ethical approval was granted for this research. The study employed a time-bound prospective design; total pregnant women (900) were categorized into those suspected of having UTI (pyuria, with or without symptoms) and those not suspected. Asymptomatic bacteriuria is diagnosed through a urine specimen with an appropriate microscopic examination, followed by culture. Results: The occurrence …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 13–20 Read article
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Image Preprocessing and Analysis on Eye Fundus Images Segmentation by Using Density Clustering Methods
Abstract: In order to do an automated evaluation of various retinal illnesses such as Diabetic retinopathy, Glaucoma, and Macular Edema, fundus images must be pre-processed first. For many reasons, it's difficult to accurately detect the optic disc. Many blood vessels cross the optic disc, making it difficult to discern the disc's boundaries in fundus images. Lesion regions in diabetic retinopathy look very much like an optic disc's colour and texture, so …
Published in Recent Trends in Sensor Research & Technology Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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Development of a Polymeric Detection System for Salivary Annexin-1: A Potential Tool for Point-of-Care Diagnostics in Periodontal Disease
Abstract: Salivary annexin-1, a protein with anti-inflammatory properties, has emerged as a potential biomarker for periodontal disease. However, current detection methods, like ELISA, are often complex and require laboratory settings. This study explores the development of a novel polymeric detection system for the rapid and sensitive identification of salivary annexin-1. This system could leverage the unique properties of polymers to create a point-of-care diagnostic tool for: (1) early detection and monitoring …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 101–110 Read article
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Design and Implementation of Automatic Flame Detection and Tracking
Abstract: Fire accidents pose important risks to life, property, and the environment, making early detection and fast suppression vital. This paper presents the design and application of an automatic flame detection and suppression system using Arduino Uno. The system uses flame devices to notice the presence and direction of flame, while the Arduino Uno processes the sensor data to control engines for sensor site and water pumping. The design joins two …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 7–14 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article
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Drug-Induced Liver Injury: Hepatotoxicity and Treatment - A Literature Review
Abstract: Drug-induced liver injury (DILI) is a major clinical and regulatory challenge, posing risks to patient safety and drug development worldwide. As the primary organ responsible for xenobiotic metabolism, the liver is particularly susceptible to toxic injury from prescription drugs, over-the-counter medications, herbal products, and dietary supplements. Drug-induced liver injury (DILI) accounts for a substantial proportion of acute liver failure cases and remains a leading cause of post-marketing drug withdrawal. Its …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 1, 2026 · pp. 1–17 Read article
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A Study to Assess the Risk Factors and Symptoms of Dialysis Disequilibrium Syndrome among Patients Undergoing Hemodialysis
Abstract: Dialysis Disequilibrium Syndrome (DDS) is a rare but potentially life-threatening neurological complication associated with hemodialysis, particularly during initiation or in high-risk patients. It is characterized by a spectrum of neurological manifestations ranging from mild symptoms such as headache and nausea to severe outcomes including seizures, coma, and death. Early identification of risk factors and prompt recognition of symptoms are crucial to prevent morbidity and mortality. The present study aimed to …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 Read article
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Sensor Guard: Thermal Sensor System for Lion Detection and Collision Prevention
Abstract: This paper presents a novel system that utilizes thermal imaging and CCTV cameras integrated with sensors to detect heat sources, specifically focusing on the detection of lions near railway tracks to prevent collisions. The system employs infrared thermal imaging to identify heat signatures of animals, particularly lions, that may create risk to his/her life. By combining thermal sensors and machine learning algorithms, the system is capable of accurately the heat …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 21–28 Read article
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Role of the Surgical-Ward Nurse in Identifying, Escalating, and Managing Postoperative Anastomotic Leak in Colorectal Patients: A Narrative Synthesis in an Australian Nursing Perspective
Abstract: Purpose: Postoperative colorectal anastomotic leak (AL) is one of the most feared complications after colorectal surgery because of its association with sepsis, reoperation, mortality, prolonged hospital stay, delayed adjuvant therapy, and permanent stoma formation. This narrative practice review outlines the frontline role of surgical-ward nurses in the early identification, escalation, and interim management of AL within the Australian acute-care context. Methods: A narrative synthesis of contemporary consensus statements, systematic reviews, …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–12 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 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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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Knowledge, Attitude, and Practice Regarding Breast Cancer and Its Prevention Among Adolescent School-Going Girls
Abstract: Introduction: Breast cancer claims the lives of over 500,000 women globally each year. In low-resource settings, most women are diagnosed at an advanced stage of the disease, resulting in low 5-year survival rates, typically ranging between 10 and 40%. However, in regions where early detection and basic treatment are both available and accessible, the 5-year survival rate for early-stage localized breast cancer can exceed 80%. Objectives of the Study: The …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–9 Read article
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Systolic-Predominant Hypertension and the Aging Heart: A Cross-Sectional Study on LVH and Cardiovascular Riskss
Abstract: Background: Systolic-predominant hypertension, defined as a systolic blood pressure ≥140 mm Hg with diastolic pressure <90 mm Hg, is the most prevalent form of hypertension in the elderly. It arises primarily due to age-related arterial stiffening and baroreceptor dysfunction. Once considered a benign outcome of aging, systolic-predominant hypertension is now recognized as a major risk factor for cardiovascular morbidity and mortality. Aim and Objective: To evaluate the cardiac status and …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 1, 2026 · pp. 13–24 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article