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57 results for “Accuracy Measures”
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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
Research ArticleOpen accessIn the abstractCrime Rate Analysis and Mapping from Socio-Economic Data Using Deep Neural NetworksSanthosh Sankara, Nadeson SugithaCrime prediction is the attempt to identify and mitigate future criminal activity. Crime is typically "unpredictable"; it cannot be predicted in advance. Addressing the roots of crime has long been a priority for researchers. Extracting causality from data is difficult if the relevant data aspects are not selected. In this research activity, an innovative classification framework is defined which is … …Journal of Computer Science, Vol. 20, Issue 10 · 17 Aug 2024 · 5,097 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic PatientBiplov Paneru, Bishwash Paneru, Krishna Bikram Shah et al.The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and refined, including Support Vector Machines (SVM), Random Forest, XGBoost, Multi-Layer Perceptron (MLP) and a hybrid model that combines MLP and SVM. To evaluate the durability of the … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,226 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,186 accessesView PDFCite
Review ArticleOpen accessIn the abstractArtificial Intelligence Techniques and External Factors used in Crime Forecasting in Violence and Property: A ReviewRebaz Mala Nabi, Soran Ab. M. Saeed, Habibollah HaronCrime forecasting is beneficial in providing useful information to authorities in planning effective crime prevention measures. The two types of analysis used in crime forecasting are univariate and multivariate. Comparatively, multivariate analysis provides better forecasting accuracy because of its ability to discover crime patterns not previously seen. Crime is strongly influenced by several external factors, including economic, social and demographic. … …Journal of Computer Science, Vol. 16, Issue 2 · 19 Feb 2020 · 7,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpowering Small Language Models With Chain of Thought and Parameter Efficient Fine Tuning for Efficient Deep ReasoningAryan Raina, Shiwani Gupta, Jagruti Jadhav et al.Small Language Models (SLMs) run faster and fit on modest hardware, yet solving multi-step logic problems has traditionally been difficult for them. This work investigates a systematic, multi-model framework that combines Chain-of-Thought (CoT) prompting with Low-Rank Adaptation (LoRA) parameter-efficient fine-tuning, and measures the contribution of each component independently. We evaluate three SLMs (TinyLlama-1.1B, Phi-3-mini-4k-instruct, and Qwen2.5-1.5B) using 1,164 training samples … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 869 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,220 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Machine Learning for the Detection of Depression and Mindfulness as a Mitigation MethodSantiago Domingo Moquillaza Henriquez, Liliana Ruth Huamán Rondón et al.Depression is a global mental health problem with various causes. Nowadays, with Artificial Intelligence, it can be predicted in order to take preventive measures, whether at a psychotherapeutic or pharmacological level. This research, based on a survey conducted, detects depression using logistic regression with a 91% fit to the ROC-AUC model, accuracy of 0.839188, precision 0.851354. In addition, a study … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,333 accessesView PDFCite