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140 articles for “early disease detection”
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Editorial: Advancements in Movement Analysis for Understanding Neurological Disorders
Abstract: Neurological disorders pose a significant challenge, demanding innovative approaches for accurate diagnosis, effective treatment, and deeper understanding. Movement analysis emerges as a powerful tool, offering a quantitative window into the complexities of motor function. This editorial delves into the transformative impact of movement analysis on neurological research and clinical practice. Traditional diagnostic methods, reliant on subjective observations, often miss subtle motor impairments, particularly in early disease stages. Movement analysis tackles …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 28–32 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Crispr Cas – Revolutionizing Modern Therapies and Beyond
Abstract: CRISPR-Cas technology has emerged as a transformative tool in modern molecular biology, revolutionizing both fundamental research and clinical applications. This RNA-guided gene-editing system enables precise and efficient genomic modifications, offering unprecedented potential for addressing genetic disorders, infectious diseases, and oncological conditions through innovative therapeutic interventions. The inherent specificity and programmability of CRISPR-Cas systems have facilitated breakthroughs in diverse fields, including precision medicine, regenerative therapies, and immuno-oncology. Beyond its therapeutic applications, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 25–38 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 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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Non-Small Cell Lung Cancer: Types, Pathogenesis, Diagnosis, and Novel Therapeutic Strategies
Abstract: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer, accounting for over 85% of all cases globally. It remains one of the primary causes of cancer-related death due to its rapid progression, few early symptoms, and late detection. The three main forms of non-small cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and giant cell carcinoma; each has a unique histology, prognosis, and response to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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A Novel Solution to Oral Hygiene
Abstract: This paper proposes a novel approach to oral health monitoring through the development of a smart toothbrush equipped with a camera, pH sensor, and temperature sensor. The integration of these sensors allows for real-time monitoring and early detection of potential oral health issues such as cavities, gum disease, pyorrhea and enamel erosion. The camera provides visual data for assessing plaque buildup and other visible signs of oral health problems, while …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 29–34 Read article
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Veterinary Immunology in Zoonotic Disease Control
Abstract: Zoonotic diseases, which are transmissible between animals and humans, pose a significant threat to global public health, food security, and economic stability. Veterinary immunology plays a pivotal role in understanding host–pathogen interactions, developing preventive strategies, and mitigating the impact of these diseases. Animals serve as reservoirs for a variety of pathogens, including viruses, bacteria, and fungi, which can persist asymptomatically or cause clinical disease. Understanding the immune mechanisms in both …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 36–43 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 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 Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Chronic Obstructive Pulmonary Disease (COPD) in Younger Adults: Challenges and Considerations – A Review
Abstract: Chronic Obstructive Pulmonary Disease (COPD) phenomenon rapidly converting into chronic significant health issues for many young adults. A disease calculated for older age gives way to early-onset COPD, which creates new issues for diagnosing and treating the illness and even interacts with the quality of life. The article reviews the epidemiology, risk factors, pathophysiology, clinical presentation, and treatment considerations related to this set of conditions. From those risk factors, early-onset …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 08–19 Read article
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Chronic Kidney Disease: A Comprehensive Review
Abstract: Chronic Kidney Disease (CKD) is a progressive condition characterized by a long-term decline in kidney function, leading to a gradual deterioration of the kidneys' ability to filter waste and maintain fluid balance. It is diagnosed when the Glomerular Filtration Rate (GFR) falls below 60 ml/min/1.73 m² or when there is evidence of kidney damage (such as proteinuria) lasting for 3 months or more. The most common causes of CKD are …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 37–42 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 Read article
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Dental and Oral Health Challenges in Patients with Eating Disorders: An Updated Review
Abstract: Eating disorders are complicated psychiatric disorders with profound systemic and oral health implications that are often not identified in clinical practice. Dietary restriction, binge eating, and self-induced vomiting are disorders eating behavior that negatively impact the oral cavity via nutritional deficiency, exposure to acid, malfunction of salivary activities, and changes in immune and microbial. These processes lead to a wide spectrum of oral and dental effects such as dental erosion, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 1, 2026 · pp. 25–34 Read article