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45 articles for “AUC”
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Comparative Evaluation of GPBB and CK-MB in Early Diagnosis of Acute Myocardial Infarction in Diabetic and Non-Diabetic Patients
Abstract: Background: Acute myocardial infarction (AMI) continues to be a leading cause of morbidity and death among people worldwide. To lower the risk of problems, early and precise diagnosis is essential, particularly for diabetes patients. The study investigates the diagnostic value of Glycogen Phosphorylase BB (GPBB), a potential early biomarker of myocardial necrosis, and compares it with CK-MB, a widely used cardiac marker, in AMI diagnosis. Inflammatory markers (hs-CRP, IL-6, TNF-α) …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 33–37 Read article
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Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients
Abstract: Background: Chronic kidney disease (CKD) is presently characterized by the presence of proteinuria and/or a diagnosis of renal impairment. The worldwide significance of CKD is underscored by the fact that its prevalence and incidence have doubled over the past three decades. This paper provides an overview of the existing evidence regarding biomarkers in individuals with CVD or CKD, with a particular focus on the emerging biomarkers (i.e., eGFR, sALB, UACR, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–12 Read article
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Polymeric Ion-Exchange Complexes of Carbomer for Taste Masking and Enhanced Drug Bioavailability: A Physicochemical and In Vivo Study
Abstract: Famotidine (FAM) was recognized as a crystalline powder that varies in color from white to pale yellow and possesses an extremely bitter flavor. This study aimed to conceal the unpleasant flavor of FAM through employing unconventional ion-exchange resins sourced from Carbomer polymer Evaluation (Carbopol 974P). We used FTIR, DSC, and XRD to look at the drug-resin combination in its hard form to learn more about its physical and chemical properties. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 727–740 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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Evaluation of Polyethylene Glycol (PEG)-Based Polymers for Improving Solubility and Bioavailability of Poorly Soluble Drugs
Abstract: A significant barrier to optimizing oral bioavailability is the inadequate water solubility of numerous pharmaceutical compounds. This study examined whether polymer systems utilizing polyethylene glycol (PEG) may enhance the solubility and bioavailability of a poorly soluble model drug. Multiple PEG polymers with molecular weights between 2,000 and 10,000 Da were utilized to produce PEGylated preparations. The formulations were subsequently evaluated for dissolution efficacy, medication loading capacity, particle size, and solubility …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 489–499 Read article
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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Using Emission Taxes as Policy Instruments for Clean Coal Technologies in Indian Coal-fired Power Plants
Abstract: AbstractRising electrification needs have led to increased coal combustion, which in turn has made India, the second highest sulphur dioxide and third highest carbon dioxide emitter. The twin task of providing electricity to 300 million citizens while meeting stringent climate change mitigation needs is a major challenge to India. Thus, a strategy for joint energy-economy growth has to be worked out. Coal-fired power plants account for around half of the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 10, Issue 1, 2020 · pp. 1–7 Read article
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A Disaggregated Optimization Approach for Competitive Procurement of Energy and Operating Reserve
Abstract: In restructured environment, Ancillary Services (AS) plays a vital role, as they are required for reliable and secure operation of the power system. Operating Reserve (OR), as one of the main AS, is a capability of a power system to prevent any unexpected imbalances caused by generation, transmission or equipment outage has been considered in this work. The approach is based on disaggregated clearing of energy and OR, which can …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 3, 2016 · pp. 33–41 Read article
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An Optimal Bidding Strategy for Social Welfare Maximization of Microgrid
Abstract: Competition in power markets implies benefit to the generators as well as customer. The uncertain nature of bids and behavior of renewables makes the bidding strategy more complex. The power market comprises of Generation companies (GENCOS), Transmission companies (TRANSCOs) and Distribution companies (DISCOs) which actively participate in the auction process. In this paper, a new bidding strategy for a microgrid in day-ahead market is proposed for social welfare maximization considering …
Published in Journal Of Network security · Vol. 8, Issue 1, 2020 · pp. 11–21 Read article
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A Hybrid Machine Learning Approach for Enhanced Patient Diagnosis and Health Outcome Prediction
Abstract: Rapid and accurate diagnosis is essential to present day practitioners of medicine, yet can be complicated by the enormous volume and complexity inherent in clinical data. To this end, we here propose a hybrid machine learning model in combination with Recursive Feature Elimination (RFE) and ensemble voting to enhance the diagnostic accuracy by integrating multiple models. Trained on real-world electronic health data, including lab results, demographics and medical history, the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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A Privacy-Preserving and Performance-Optimized Machine Learning Framework for Personalized E-Commerce User Experience
Abstract: In contemporary e-commerce websites, merchant suggestions are the most outstanding way to boost customer satisfaction and conversion levels. Nevertheless, the growing dependence on user data provokes significant concerns over the protection of privacy and efficiency in computation. In this paper, we have suggested a privacy-preserving and performance-optimized machine learning framework that allows customized e-commerce experiences and protects the sensitive information of users. The framework incorporates the concepts of federated learning …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 1–8 Read article
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A Predictive Analytics Model for Maximising Profit in e-commerce Companies
Abstract: AbstractPredictive analytics have become a crucial aspect for many e-commerce companies. The primary objective of this work is to apply and compare different machine learning techniques to build an efficient and accurate predictive model for the analysis and identification of customers who are expected to purchase again in the next 90 days. The main performance goal of the predictive model is to maximize profit for the e-commerce company by providing …
Published in E-Commerce for Future & Trends · Vol. 4, Issue 2, 2017 · pp. 10–23 Read article
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Improved Melanoma Recognition using Score Fusion Framework based on Deep Classifiers
Abstract: Melanoma is a fast-growing and malignant cancer that affects neural crest-derived cells of the skin. Early detection is the key to survival and rapid recovery; however, typical diagnosis is based on visual inspection by expert dermatologists. Many melanoma recognition methods have been proposed in the literature that can classify lesions, based on hand-crafted as well as deep learning-based features. However, an accurate, automated method for melanoma is still required. This …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 2, 2021 · pp. 25–33 Read article