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135 articles for “early detection”
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Review ArticleOpen accessIn the abstractUnveiling Skin Cancer: A Review of Deep Learning Techniques for DetectionGoutham Lal Shanmughamadom Harilal, Tamilselvi PanneerselvamEarly identification is essential for successful treatment and better patient outcomes since skin cancer is caused by damage to DNA in skin cells, which can result in genetic abnormalities and the possibility of metastasis. The present systematic review scrutinizes the efficacy and obstacles of early detection techniques, which differentiate between benign and malignant lesions by examining lesion attributes such as … …Journal of Computer Science, Vol. 21, Issue 9 · 23 Oct 2025 · 2,609 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature ConcatenationMuhammad Ahtsam Naeem, Muhammad Asim Saleem, Jarrar Amjad et al.The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to have significant leaf disease. Early Blight and Late Blight are two prevalent leaf diseases that affect potato plants. The early detection … …Journal of Computer Science, Vol. 21, Issue 5 · 12 May 2025 · 5,178 accessesView PDFCite
Research ArticleOpen accessIn the abstractMethodological Approach to Developing a Model of Interference-Free Processing of Multichannel Records of the Electrical Cardiological Impulse to Determine Episodes of Cardiac Muscle IschemiaSergey Alexandrovich Sheptunov, Alexander Nikolaevich Muranov, Abas Khasanovich Lampezhev, Tagirbek Gaidarbekovich AslanovThis study considered a set of topical issues aimed at improving the methodology of the early recognition of episodes of myocardial ischemia. It aims to solve a set of problems in the substantiation and development of a methodological approach for building a model of interference-free processing of multichannel electrocardio signal recordings. Based on theoretical and experimental studies, this will create … …Journal of Computer Science, Vol. 21, Issue 5 · 14 Apr 2025 · 4,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusing CNN Models for Improved Parkinson’s Disease Detection from Handwritten FeaturesSabrina Benredjem, Tahar MekhazniaNeurodegenerative Diseases (NGD) are a group of progressive neurological disorders, including cognitive decline as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) that result in the progressive loss of neuronal structure or function. This can lead to a variety of symptoms, in this study we are interested in PD one of the neurological diseases that causes the loss of dopamine-producing neurons … …Journal of Computer Science, Vol. 21, Issue 2 · 22 Jan 2025 · 6,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransforming Retinal Diagnostics: Advanced Detection of Diabetic Retinopathy Using Vision Transformers and Capsule NetworksVishal Sharma, Rishu, Vinay Kukreja et al.Diabetic Retinopathy (DR), nowadays is one of the leading causes of blindness worldwide, it is a severe complication of diabetes mellitus that affects the retina blood vessels. Accurate diagnosis depends on early detection of DR. The study aims to develop a hybrid model that is the combination of a Vision Transformer and Capsule Network (ViT-CapsNet) to classify the DR at … …Journal of Computer Science, Vol. 21, Issue 2 · 14 Jan 2025 · 6,765 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,537 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach Based on Federated Learning for the Identification of Man in the Middle Attacks in IOT Networks Using BlockchainSarumathi S, Juliet Johny, Minal Khandare et al.Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning’s … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,618 accessesView PDFCite
Research ArticleOpen accessIn the abstractTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,889 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Optimized Machine Learning Approach for Early Prediction of Heart Disease Using Bio-Inspired AlgorithmsIndira Priyadarsini, I.S. Siva Rao, P. Swetha et al.This study presents a novel approach for early prediction of heart disease using bio-inspired optimization algorithms to select and optimize features. The proposed approach utilizes a Genetic Algorithm (GA), Bat Algorithm (BA), Bee Algorithm (BA), and Ant Colony Optimization (ACO) to optimize a set of four features for improved prediction accuracy. The optimization process aims to identify the most relevant … …Journal of Computer Science, Vol. 21, Issue 1 · 4 Dec 2024 · 5,235 accessesView PDFCite