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45 articles for “AUC”
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Investigating the Dietary Flexibility and Feeding Behavior of Clarias anguillaris and Auchenoglanis biscutatus in a Tropical River Ecosystem
Abstract: Studies on food and feeding habits of fishes are required to guide the selection of fish species for culture. The current study determined the food and feeding habits of Clarias anguillaris and Auchenoglanis biscutatus in the Lower River Benue at Makurdi, Nigeria. Fish samples were collected biweekly from local fishermen at the Wadata landing site who fished with different gears like gillnets, cast nets, hook and line, traps and lift …
Published in International Journal of Marine Life · Vol. 2, Issue 1, 2025 · pp. 1–9 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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A Novel Hybrid Link Prediction Algorithm for E-Commerce Recommender System Based upon Common Neighbor and Resource Allocation Methods
Abstract: Link prediction is a challenging task in recommender systems, as it requires the ability to accurately predict future links between users and items. In this study, we propose a novel hybrid link prediction algorithm for e-commerce recommender systems that combines the common neighbor and resource allocation methods. The common neighbor method is a straightforward and intuitive algorithm that calculates the number of shared neighbors between two nodes. The intuition is …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 12–17 Read article
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Detecting Fake Accounts on Social Media Using Machine Learning
Abstract: The growing frequency of fake accounts on social media platforms underscores the critical necessity for effective detection methods. In response to this challenge, our study leverages state-of-the-art machine learning techniques to identify and counter deceptive entities effectively. By conducting a thorough analysis of social media data, our approach unveils intricate patterns indicative of fraudulent accounts, enabling proactive measures against them. Through the application of advanced algorithms, we present a comprehensive …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 21–32 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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A Model of Bidding in Rotating Saving Credit Associations
Abstract: The paper analyzes bidding behavior in discount bidding Roscas under the assumption of risk neutrality. Roscas are group based revolving financial schemes. In discount bidding Roscas, individuals bid for a lumpsum. We find that bids submitted by members in equilibrium are increasing in the returns or opportunities for investment. Further, members submit lower bids when credit is available outside Rosca at expensive rates. A bidding Rosca is efficient as an …
Published in Journal of Production Research & Management · Vol. 7, Issue 1, 2017 · pp. 11–15 Read article
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Comparison between two severity classificaitons in patients with acute cholecystitis
Abstract: Background and objective: Assessment severity helps clinicians to guide appropriate treatment and minimumize adverse outcome. The objective of our study was to comparison between TG13 severity system and EGS grade system for predicting clinical outcomes in acute cholecystitis. Patients and method: This is a retrospective single-center study which enrolled patients who were admitted to pyongsong medical university hospital between February 2020 and October 2021. Tokyo 2013(TG 13) severity classification and …
Published in Research and Reviews : Journal of Surgery · Vol. 12, Issue 2, 2023 Read article
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An Anthology of Parametric ROC Models
Abstract: In the context of classification problems, ROC curve has gained its importance in classified fields. The so called parametric form of ROC curve, namely, Binormal ROC model was developed by assuming normal distributions. However, the practical situations in classifying individuals/objects demanded new forms of ROC models. The present paper brings out an insight into the theoretical development of different parametric forms of ROC models and its measures.
Published in Research & Reviews : Journal of Statistics · Vol. 5, Issue 2, 2016 · pp. 32–46 Read article
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Accelerate Drug Development with Pharmacokinetic Softwares
Abstract: During continuously evolving technologies and mechanized equipments, there has been a tremendous growth in the pharmaceutical sector over the past few decades. New technologies, software, devices, and techniques are being developed or researched upon with each passing day. By leveraging pharmacokinetic software, researchers can efficiently analyze vast datasets from preclinical and clinical studies, extracting actionable insights that inform decision-making early in the development cycle. This predictive capability not only accelerates …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 26–40 Read article
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Predictive value of Systemic Inflammatory Response Syndrome score in assessing the clinical outcomes in patients with acute pancreatitis
Abstract: Background: The role of various clinical scoring systems to assess the severity and outcomes of acute pancreatitis is attracting a lot of attention to the experts. Purpose: We aimed to objectively reconfirm the predictive value of systemic inflammatory response syndrome (SIRS) score for predicting the various clinical outcomes of acute pancreatitis and also to evaluate the significance of monitoring SIRS score on day 1 and its duration. Methods: We retrospectively …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 11, Issue 1, 2022 · pp. 34–42 Read article
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Application of Resource Allocation Similarity Based Link Prediction in Wireless Networks
Abstract: Link prediction in wireless networks plays a crucial role in predicting missing connections within multiplex networks. This study focuses on the utilization of similarity-based link prediction methods in wireless networks. These methods assume that the likelihood of linkage between nodes is determined by their similarity, based on shared features. Several similarity measures, such as Common Neighbors (CN), Preferential Attachment (PA), Adamic-Adar (AA), and Resource Allocation (RA) indices, are commonly employed …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 37–42 Read article
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The Evaluation of the Light Parameters and Pleural Fluid Cholesterol to Determine the Differences Between Exudative and Transudative Pleural Discharge
Abstract: Background: Pleural effusion occurs when an imbalance between pleural fluid production and absorption leads to the accumulation of excess fluid in the pleural cavity. Pleural effusions are commonly classified into two types: transudative or exudative, depending on the underlying mechanism of fluid formation. While transudates typically result from systemic factors like heart failure or liver cirrhosis, exudates are usually caused by local factors such as infection, malignancy, or inflammation. Differentiating …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 30–35 Read article
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The Prognostic Efficacy of Inflammatory Indicators in Determining the Cause of Multiple Sclerosis Exacerbation
Abstract: Multiple sclerosis (MS) is the most prevalent immune-mediated inflammatory disease affecting the central nervous system, presenting with diverse clinical symptoms and manifestations. This study investigates the diagnostic potential of the monocyte-to-lymphocyte ratio (MLR), red cell distribution width-to-lymphocyte ratio (RLR), and systemic immune-inflammation index (SII) in detecting MS attacks among relapsing-remitting MS (RRMS) patients seeking care in the emergency department (ED). The research focused on RRMS patients who presented to the …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 1, 2025 · pp. 1–8 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article