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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
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
Research ArticleOpen accessIn the abstractAlgorithmization of Electrostatic Model for Solving the Direct Problem of ElectrographyTagirbek Gaidarbekovich Aslanov, Naur Zamirovich Ivanov, Shamil Shamil`evich Anudinov, Tatiana Vladimirovna KarlovaAn analysis of the creation and implementation of algorithms to control cardiological processes occurring in the cardiovascular system using software and hardware diagnostic systems is a required activity. This study considers ways to improve the methods of medical data processing using electronic diagnostic systems, relying on existing methods of mathematical simulation of human body states. This study describes the development … …Journal of Computer Science, Vol. 21, Issue 4 · 7 Mar 2025 · 5,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 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 · 6,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of the Presence of the "Swollen Shoot" Disease in Endemic Areas in Côte d'Ivoire Via Convolutional Neural NetworksCoulibaly Mamadou, Silue Kolo, Konan Hyacinthe Kouassi et al.The detection of Swollen Shoot disease and its control is one of the major objectives of research related to sustainable cocoa farming in Côte d'Ivoire. To contain the epidemic, the Cocoa Coffee Council (CCC) in collaboration with the National Agency for Support to Rural Development (ANADER) is responsible for prospecting and delimiting the infected areas as well as for uprooting … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 3 · 1 Oct 2023 · 6,064 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractKnowledge Based Bayesian Network Construction Algorithm for Medical Data Fusion to Enhance Services and DiagnosisAhmed SamehTraditional Bayesian networks' algorithms are treating the network construction process as an isolated and autonomous data-driven trial-and-error process and completely ignoring the domain knowledge. In this work we are proposing a new 'Semantically Aware Ontology-Based Bayesian Network construction algorithm' that is knowledge centered instead of data centered. The objective of the new algorithm is to empower patients through improving their … …Journal of Computer Science, Vol. 15, Issue 5 · 28 May 2019 · 8,035 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCObc-ST: An Improved Clinical Reasoning Algorithm Based on Select and Test (ST) Algorithm for Diagnosing Breast CancerOlaide Nathaniel Oyelade, Sunday Adeyemi AdewuyiThe need for an accurate reasoning algorithm is usually necessitated by the sensitivity of domain of (medicine as example) application of such algorithms. Most reasoning algorithms for medical diagnosis are either limited by their techniques or accuracy and efficiency. Even the Select and Test (ST) algorithm which is considered a more approximate reasoning algorithm is also limited by its approach … …Current Research in Bioinformatics, Vol. 8, Issue 1 · 15 Apr 2019 · 7,162 accessesView PDFCite