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340 articles for “interpretation”
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Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data
Abstract: Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 315–324 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Evolving IoT: Based Smart Healthcare Monitoring System
Abstract: The continuous progress in technology has led to remarkable enhancements in various aspects of human life, including healthcare. Within the healthcare sector, practitioners and experts are embracing new technologies to significantly improve the implementation of medical services. The Internet of Things (IoT) has emerged as a crucial foundation for various innovative healthcare technologies, such as heartbeat sensors, ECGs, and blood pressure sensors, each equipped with microcontrollers to read and interpret …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 1, 2023 · pp. 17–27 Read article
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Recent Update on Advanced Drug Delivery System
Abstract: Over the past decade, there has been a growing interest in the use of artificial intelligence (AI) technology for analysing and interpreting biological or genetic data, accelerating drug discovery, and identifying selective small-molecule modulators or rare molecules in addition to predicting their behaviour. The use of artificial neural networks (ANNs) for the rapid analysis of massive amounts of data, the development of novel hypotheses and treatment plans, the prediction of …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 22–30 Read article
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Section Cutting in Histopathology: An Update
Abstract: Histopathology is the microscopic examination of tissues to diagnose and study diseases, more significantly the diagnosis of cancer. It plays a pivotal role in modern medicine, serving as the gold standard for definitive diagnosis in a wide range of conditions. Through meticulous analysis of tissue morphology (structure) and cellular characteristics, histopathology provides crucial information for disease classification, staging, and guiding patient management. In the world of histopathology, where microscopic details …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 1, 2024 · pp. 29–34 Read article
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Planetary Portraits: Understanding Astrological Charts
Abstract: Astrology, as an ancient and complex system of divination, has always held an intriguing place in human culture. This study explores the fundamental ideas behind interpreting astrological charts, with a special emphasis on planetary portraiture. The aim is to elucidate the significance of planetary positions, aspects, and their astrological interpretations in creating a comprehensive portrayal of an individual's personality traits, life events, and potential destinies. Through an exploration of astrological …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 1, 2024 · pp. 22–26 Read article
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Report Pulse: Using Machine Learning
Abstract: This study presents the development of a novel medical report analyzer, specifically designed to streamline the interpretation of complex health data. The Report Pulse project represents a significant advancement in healthcare innovation, aiming to facilitate deeper insights into medical reports and foster personalized health management strategies. At its core, the Report Pulse project introduces a sophisticated blood report analyzer, which transcends conventional data analysis by providing actionable insights tailored to …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 28–33 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Applying Text Analysis Methods for Emotion Recognition
Abstract: This article presents a comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 12–22 Read article
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Glitches in the Implementation of Bioinformatics in Medical Settings: A Comprehensive Review
Abstract: Bioinformatics is a dynamic field at the intersection of biology, computer science, and information technology, offering new possibilities in medicine by enabling a deeper understanding of genomics, molecular biology, and personalized treatment approaches. Its integration into healthcare could greatly enhance diagnostics, enable tailored treatments for individuals, and facilitate the analysis of large biological datasets. However, despite its potential, several barriers impede its successful implementation in clinical settings. These include technical …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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Statistical Methods in Law: Analysing Trends and Patterns in Judicial Outcomes
Abstract: The research paper explores the integration of statistical techniques within the domain of legal science, emphasizing their role in assessing and interpreting ongoing trends. By employing methods such as descriptive statistics, inferential statistics, and multivariate analysis, the study highlights how empirical data can effectively uncover disparities in areas like sentencing practices, risk assessments, and the evaluation of policy outcomes. These statistical tools enable researchers and legal professionals to identify patterns, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 32–36 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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English Literature in the Digital Era: Transformations and Trends
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 27–32 Read article
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Sensor Technologies in Robotics: A Review of Vision, Tactile, and Proximity Sensing Systems
Abstract: Robotics has undergone remarkable advancements in recent decades, largely driven by the integration of cutting-edge sensor technologies. Sensors serve as crucial for allowing robots to precisely logic, interpret, and react to the world around them. Among the most essential sensor types used in robotics are vision sensors, tactile sensors, and proximity sensors. These technologies strengthen a robot’s capacity for successful navigation, for example, object manipulation, and contact with people and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Graphs and Their Real-Life Applications in Pharmaceutical Research
Abstract: This study provides a comprehensive overview of the role of graphs in pharmacy research, emphasizing their significance as powerful tools for data visualization, interpretation, and communication. In the field of pharmacy, research often generates large volumes of complex data related to drug development, pharmacokinetics, pharmacodynamics, medication safety, and patient outcomes. Graphs serve as an essential medium to translate these data into accessible, interpretable, and actionable insights, supporting evidence-based practice and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 01–08 Read article