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68 results for “Disease Prediction”

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Research ArticleOpen accessIn the abstractAn Integrated Disease Progression Model to Analyze Electronic Health Records With Multimodal Datasets Using Deep Learning TechniquesThulaganyo Dimakatso, Venumadhav Kuthadi, Rajalakshmi Selvaraj, Othapile DinakenyaneIn contemporary clinical environments, precisely simulating the emergence of disease is an intricate task owing to heterogeneously derived data and variability in the record of diagnoses. The research presents a stable classification model that integrates image data with formalized patient data to track patterns in disease through various stages. The suggested approach combines a multi-stage analytical methodology that includes systematic … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,678 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn AI-Powered Integrated Care Model Combining Traditional Chinese Medicine and Western Medicine for Personalized Alzheimer’s Disease ManagementShurong Li, Yiming Chen, Jin Xu et al.Alzheimer's Disease (AD) gradually reduces memory and cognition. While Western medicine focuses on pharmacological treatments, it frequently ignores holistic factors such as mood and digestion. Traditional Chinese Medicine (TCM) addresses these issues through a wellness-oriented approach. However, the combination of both systems in patient care is uncommon. Current Alzheimer's disease treatments are often siloed, relying solely on Western or alternative … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 2,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Deep Learning to Support Clinical Decision-Making: The Case of Alzheimer’s Disease DiagnosisNawal Mohamed Bahy Eldin, Ghada A. El Khayat, Abeer A. AmerAlzheimer’s disease is a chronic, progressive brain disorder that leads to a gradual decline in memory and cognitive functions. In this study, N-VGG16, an advanced deep learning model, is proposed. The model builds upon the VGG16 architecture, incorporating key enhancements to improve its ability to classify neurodegenerative conditions. The model processes structural neuroimaging data using a refined pipeline that applies … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,383 accessesView PDFCite
Research ArticleOpen accessIn the abstractMolecular Characterization and in Silico Analysis of Phytochemical Compounds from Plants with Immunomodulatory PotentialHermin Pancasakti Kusumaningrum, Rejeki Siti Ferniah, Siti Nur Jannah et al.The immune system works to protect the body against foreign antigens from microorganisms and abnormal cells. The use of herbal plants as immunomodulators are used to prevent disease attacks. TNFα and interleukin-6 are pro-inflammatory immune systems that cause disease in uncontrolled synthesis. Herbal plants as inhibitors of TNFα and interleukin-6 need to be identified molecularly to reduce the occurrence of … …OnLine Journal of Biological Sciences, Vol. 25, Issue 3 · 27 Nov 2025 · 1,954 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,900 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,533 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 · 3,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,765 accessesView PDFCite