Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

199 articles for “Prediction Models”
Set a search alert
Also matching:4 special issues
Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractEarly Diagnosis of Parkinson's Disease Through Voice Analysis and Machine LearningAmrita Naik, Mohd Sahil Khan, Akhilesh Manoj Saraf et al.Parkinson’s Disease (PD) is a progressive neurological disorder, and its prevalence has increased considerably in recent years. Early and accurate diagnosis plays a crucial role in effective treatment, but identifying the disease in its early stages remains challenging, especially for non-specialist clinicians. This study presents a predictive analytics framework for detecting Parkinson's disease using voice-based features. To improve the diversity … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 652 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 920 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing the Comparative Effectiveness of Ensemble CatBoost Versus XGBoost Models in Predicting Heart Disease OutcomesManivannan D., G. Gifta Jerith, G. Chandra Sekhar et al.Cardiovascular Diseases (CVDs) are a common form of heart disease that remains a significant global cause of mortality, responsible for more than 30% of all fatalities. Without intervention, the global fatality count is projected to reach 22 million by 2030. Arterial plaque buildup may impede blood flow, potentially causing heart attacks or strokes. A combination of risk causes, including lack … …Journal of Computer Science, Vol. 22, Issue 4 · 4 May 2026 · 1,552 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Robust Ensemble Convolutional Neural Networks for Diagnosing Chest DiseasesMansour Ali Alhlalat, Ahmad Abdel-Aziz Sharieh, Mohammed Belal Al-ZoubiRadiologists employ X-ray images to differentiate various chest diseases. Given the intricate and meticulous nature of this diagnostic procedure, the assistance of automated models becomes imperative in detecting and diagnosing diseases from X-ray images. This research paper proposed a novel approach called Ensemble Convolutional Neural Network for Diagnosing Chest Diseases (ECDCNet), aimed at accurately and efficiently diagnosing fifteen different chest … …Journal of Computer Science, Vol. 19, Issue 12 · 27 Oct 2023 · 5,108 accessesView PDFCite
Review ArticleOpen accessIn the abstractCrime Prediction Using Machine Learning: A Comparative AnalysisAbdulrahman Alsubayhin, Muhammad Ramzan, Bander AlzahraniIn the past few years, Machine Learning (ML) methods have acquired extensive attention from researchers and even criminology practitioners for their potential in crime prediction and crime forecast. To date, many research studies have already been performed on crime prediction using machine learning techniques. Some common methods that have been used include KNNs, Decision trees, Naïve Bayes, and random forest, … …Journal of Computer Science, Vol. 19, Issue 9 · 29 Aug 2023 · 8,065 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Multi-Layer Perceptron in Ensemble Using Random Search for Bankruptcy PredictionBambang Siswoyo, Zuraida Abal Abas, Ahmad Naim Che Pee et al.A corporation is in financial trouble if it has money problems but has yet to be bankrupt. Companies' financial woes must be identified early to implement various bankruptcy avoidance strategies. This study discusses the optimization of the multi-layer perceptron ensemble stacking classifier hyperparameter by majority voting as a methodology for constructing a classification model for bankruptcy prediction (MLP-STM). The primary … …Journal of Computer Science, Vol. 19, Issue 2 · 5 Feb 2023 · 7,240 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 abstractA Combined Deep Learning Model with Attention Mechanism for Detection of Implant Manufacturer Using X-Ray ImagesAttar Mahay Sheetal, K. SreekumarShoulder replacement surgery is one of the invasive techniques in orthopedic disciplines that replaces dead shoulder joints with prostheses made from polyethylene and metal components. To perform the surgery, there is a need to know the implant accessories and manufacturer of the implant. Some problems arise in a situation where the patient experiences pain and shoulder malfunctions that need replacement, … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,257 accessesView PDFCite