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349 results for “Model Evaluation”
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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 abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,934 accessesView PDFCite
Research ArticleOpen accessIn the abstractResearch on Deep Neural Network for Afaan-Oromo Language Text-to-Speech SynthesisDiriba Gichile Rundasa, Arulmurugan Ramu, Teshome Debushe Adugna et al.Text-to-speech synthesis is the automatic translation of unlimited natural language sentences from Text to spoken form that closely mimics the spoken form of the same Text by a native speaker of the language. The purpose of a Texttext-to-speech synthesizer is to generate comprehensible, natural signalling human voice from text transcriptions. Despite the wide range of potential applications for Text-to-speech systems, … …Journal of Computer Science, Vol. 21, Issue 5 · 14 Apr 2025 · 7,346 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 622 accessesView PDFCite
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 abstractAdvanced Facial Emotion Recognition Using DCNN-ELM: A Comprehensive Approach to Preprocessing, Feature Extraction and Performance EvaluationBoopalan K., Satyajee Srivastava, K. Kavitha et al.As a subfield of affective computing, Facial Emotion Recognition (FER) teaches computers to read people's facial expressions to determine their emotional state. Because facial expressions convey 55% of an individual's emotional and mental state in the whole range of face-to-face communication, Facial Emotion Recognition is crucial for connecting humans and computers. Improvements in the way computer systems (robotic systems) interact … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Neural Networks Towards Electronic Trust QuantificationSmitha Zacaria, Tiny du ToitTrust is a broad term applicable in various contexts. Trust between electronic entities is complex to quantify, particularly in intricate networks. Traditional trust algorithms rely on historical trust values, requiring storage and access to past transaction details. Contextual variations further complicate trust calculation. Challenges in calculating trust include heightened computational complexities, managing information storage, and securing access to extensive datasets … …Journal of Computer Science, Vol. 20, Issue 11 · 26 Sep 2024 · 4,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Garbage Classification Using Balanced and Unbalanced Dataset with EfficientNetV2B1 ArchitectureRetinderdeep Singh, Chander Prabha, Ayman Noor et al.This research concentrates on EfficientNetV2B1 deep learning model to classify garbage collection tasks, with both balanced and unbalanced dataset configurations. The dataset includes 7,260 images for the balanced dataset and 15,515 for the unbalanced one, both of the datasets are used to train and evaluate the model. Training and evaluation of the deep learning model with the standard performance variables: … …Journal of Computer Science, Vol. 20, Issue 10 · 27 Aug 2024 · 5,091 accessesView PDFCite
Review ArticleOpen accessIn the abstractThe Impact of Di-2-Ethylhexyl Phthalate (DEHP) in Focus on the Reproductive System and Toxicity in Rat or Mammalian ModelVenkataramanaiah Poli, Srinivasulu Reddy MotireddyAbsalan, F., Saremy, S., Mansouri, E., Moghadam, M. T., Moghadam, A. R. E., & Razie, G. (2016). Effects of Mono-(2-Ethylhexyl) Phthalate and Di-(2-Ethylhexyl) Phthalate Administrations on Oocyte Meiotic Maturation, Apoptosis and Gene Quantification in Mouse Model. Cell Journal, 18(4), 503–513. https://doi.org/10.22074/cellj.2016.4717 Acevedo‐Rodriguez, A., Kauffman, A. S., Cherrington, B. D., Borges, C. S., Roepke, T. A., & Laconi, M. (2018). Emerging … …American Journal of Pharmacology and Toxicology, Vol. 19, Issue 1 · 6 Jun 2024 · 12,990 accessesView PDFCite