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478 articles for “interpretability”
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AI Based Dental Care Solution System
Abstract: The AI-Based Dental Care Solution System is a web-based healthcare application developed using the MERN stack (MongoDB, Express. js, React.js, and Node.js) and integrated with Artificial Intelligence techniques to support early and accessible dental self-assessment. The system assists users in preliminary dental consultation by collecting symptoms such as tooth pain, sensitivity, swelling, bleeding gums, and bad breath through both structured forms and a conversational chatbot interface. Using Natural Language Processing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 2, 2026 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Transforming Healthcare Through Big Data: Applications, Challenges, and Future Perspectives
Abstract: Healthcare institutions produce substantial amounts of information through electronic health records, laboratory systems, medical imaging technologies, patient monitoring devices, and various digital healthcare platforms. Managing and interpreting these continuously growing datasets through conventional approaches can be difficult and time-consuming. Big Data technologies offer advanced methods for storing, processing, and analyzing healthcare information efficiently, enabling healthcare professionals to obtain valuable insights for clinical and administrative purposes. This review explores the growing …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–9 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Bioinformatics and Medicine: Bringing Data to the Bedside
Abstract: From being an empirical and experience-based practice, modern medicine has transformed into a codified and research-based discipline, known as Evidence-Based Medicine (EBM). Though EBM has greatly enhanced the quality of medical practice through population-scale clinical trials, it still has limitations in managing biologically diverse patient populations, especially when dealing with clinical outliers who respond in an unusual way to standard treatments. With the rapid progress in genomics, proteomics, and high-throughput …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 · pp. 41–46 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Physics-Informed Machine Learning and Multiscale Modeling for Structure–Property Quantification of Polymer Composites
Abstract: The growing need for light-weight, high strength, and sustainable polymer composites has led to the development of smart methods that enable accurate structural-property quantification and material design. However, conventional methods have been predominantly data-based, thus ignoring physical constraints as well as multi-scale interactions involving fiber, matrix, interface, and process parameters, leading to lower accuracy and poor robustness and interpretability of the models. In this study, a Cat Swarm Optimization-Tuned Physics-Informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Box Plots: An Introduction to the Visual EDA Wonder
Abstract: A box plot, also known as a box-and-whisker plot, is a widely used statistical graphic that provides a concise summary of the distribution of numerical data. By displaying key descriptive measures such as the median, quartiles, interquartile range (IQR), minimum and maximum values, and potential outliers, box plots allow researchers to quickly understand the spread and central tendency of a dataset. They are especially useful when comparing distributions across multiple …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 20–30 Read article
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Unveiling Actionable Pathogenic Genes for Precision Oncology in Brain Cancers: Glioblastoma and Astrocytoma
Abstract: Glioblastoma (GBM) and astrocytoma are aggressive primary brain tumors characterized by significant molecular heterogeneity, complicating effective treatment. This study employed targeted next-generation sequencing of 529 cancer-associated genes on matched tumor-normal pairs from GBM and astrocytoma patients. Somatic variants were identified using a rigorous bioinformatic pipeline adhering to GATK Best Practices, with variant allele frequencies (VAF) calculated to assess clonal dominance. Functional annotation and driver mutation classification were performed using Ensemble …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 43–59 Read article
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Role of Artificial Intelligence in Quantum Materials Research
Abstract: Quantum materials have emerged as a transformative class of advanced materials due to their extraordinary electronic, magnetic, optical, and topological properties governed by quantum mechanical phenomena. These materials are expected to revolutionize next-generation technologies such as quantum computing, spintronics, superconducting electronics, nanoelectronics, intelligent sensing systems, and energy-efficient devices. However, conventional methods for discovering and optimizing quantum materials are often expensive, time-consuming, and computationally intensive because of the enormous complexity of …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 2, 2026 · pp. 13–27 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Traffic Density Estimation Using Image Frames in Python
Abstract: Traffic congestion is a critical challenge in modern urban environments, leading to significant delays, environmental pollution, and increased accident rates. With the rapid growth of vehicle populations in metropolitan areas worldwide, the need for intelligent and automated traffic monitoring systems has become increasingly urgent. Traditional monitoring approaches, such as inductive loop detectors and manual surveillance, are limited in scalability, deployment cost, and adaptability to dynamic traffic scenarios. This paper presents …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 38–45 Read article
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IS-Aligned Strategic Evaluation of Fire Protection Systems for Improving Fire Safety in Mixed-Occupancy High-Rise Buildings
Abstract: This paper presents a substantially reworked Indian-context evaluation of fire protection systems in a 14-building high-rise sample from Indore. The study reuses the original field dataset but replaces the earlier code mix with an explicitly IS-aligned and NBC-oriented analytical framework. Physical observation, document review and interview inputs were screened against requirements related to means of egress, compartmentation, fire detection and alarm, hydrants and hose reels, extinguishers, emergency lighting, smoke control, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 · pp. 15–26 Read article
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Advancements in Analytical Techniques and Validation Methods for Pharmaceutical Tablet Formulations Using HPTLC
Abstract: High Performance Thin Layer Chromatography (HPTLC) is a versatile analytical technique which has been effectively used for pharmaceutical quality control and cost effectively, rapidly, and high throughput analyzed tablet formulations. HPTLC is different from traditional chromatographic methods as multi sample analysis is possible in one run with low consumption of solvent, which are principles of green analytical chemistry. But existing HPTLC is limited in sensitivity, resolution and reproducibility and these …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 3, 2026 Read article
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A Five-Layer Architectural Framework for Sustainable and Scalable AI Systems
Abstract: Artificial Intelligence (AI) is not only about algorithms. AI works like a full “stack” of layers, from electricity to real-world user applications. In this paper, we explain a simple and student-friendly Five- Layer Architecture of AI: (1) Energy, (2) Chips, (3) Infrastructure, (4) Models, and (5) Applications. Each layer supports the next layer, like a cake with multiple layers. If any layer is weak, AI systems become slow, costly, or …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Artificial Intelligence in Trigonometry: Innovations, Applications, and Future Prospects
Abstract: Artificial Intelligence (AI) has transformed numerous scientific fields, yet its integration with classical mathematics such as trigonometry is still emerging. This paper explores how AI enhances trigonometric problem solving, learning, and real-world applications. We analyse AI-driven tools for teaching trigonometry, AI in geometric and spatial reasoning, usage in robotics and computer vision, and future directions for research. Key challenges, methodologies, and case studies are discussed to provide a comprehensive overview …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article