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360 articles for “prediction tool”
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Autism Spectrum Disorder Prediction Using Classification Techniques: A Comparative Analysis
Abstract: Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder marked by difficulties in social interaction, communication, and repetitive behaviors. Identifying and addressing ASD early is essential for enhancing the quality of life for those affected. Data mining techniques have emerged as powerful tools in analyzing large datasets to predict and diagnose ASD, aiding in early identification and intervention. This article presents a comprehensive comparative analysis of classification techniques employed in …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 66–71 Read article
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Tools and Techniques for Whole-Genome Alignments
Abstract: The prediction of evolutionary relationships between two or more genomes at the nucleotide level is known as whole-genome alignment (WGA). It possesses characteristics of both gene orthology prediction and collinear sequence alignment. WGAs are useful for genome-wide analyses like phylogenetic inference, genome annotation, and function prediction. So many solutions have been developed despite the fact that this problem is difficult. This article provides an overview of the approaches used to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 2, 2022 · pp. 36–38 Read article
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The Contribution of A. I. in Pharmaceutical Software
Abstract: The integration of Artificial Intelligence (AI) in pharmaceutical software has significantly transformed drug development, regulatory processes, and clinical management. AI-powered tools are revolutionizing data analysis, predictive modeling, and decision-making, enhancing the efficiency and accuracy of drug discovery and development. This article explores the multifaceted contributions of AI to pharmaceutical software, including its applications in drug screening, personalized medicine, clinical trial optimization, and regulatory compliance. Additionally, we examine how AI is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
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An Efficient LoRa-Enabled Fault Detection Using Self-Powered IoT Device
Abstract: This study describes a revolutionary internet of things (IoT) solution for effective defect detection in a variety of applications. By utilizing an IoT device that generates energy from the surroundings, the suggested solution gets around the drawbacks of conventional battery-operated gadgets. The suggested approach makes use of a self-sustaining IoT gadget that can capture energy from the surroundings to get beyond the drawbacks of conventional battery-powered IoT devices. Longer functioning …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–13 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Clinical metabolomics: Useful insights, perspectives, and challenges.
Abstract: Metabolomics provides a comprehensive snapshot of smallmolecule intermediates and end products of cellular processes and thereby links genotype, environment, and phenotype in human disease . Over the last decade, advances in liquid chromatography–mass spectrometry (LC–MS) and nuclear magnetic resonance (NMR) spectroscopy have enabled high-throughput profiling of thousands of metabolites from microliter volumes of clinical samples . Clinical metabolomics is now emerging as a tool for disease diagnosis, risk prediction, therapeutic …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 1, 2026 · pp. 29–37 Read article
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ALADIN and its Protein Interactions with the Nucleoproteins: An Insilico Analysis
Abstract: The nuclear pore complex (NPCs) are big, protein complexes made up of multiple units that traverse the nuclear envelope (NE), establishing a discerning channel between the cytoplasm and nucleus for the nucleocytoplasmic transport. It has different roles in cellular processes, like cell-cycle progression, control of gene expression, and signal transduction. NPC is a vast and complex structure, compiled from almost 30 proteins, termed nucleoporins. Earlier studies have shown that each …
Published in Research and Reviews : Journal of Computational Biology · Vol. 7, Issue 1, 2018 · pp. 28–31 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Unlocking The Bioactivity Potential: Molecular Insights and Predictions of Salen, Salophen, Allicin, Curcumin, and Piperine
Abstract: In this work, the prediction of the biological activity of several significant molecules, including salen, salophen, allicin, curcumin, and piperine, are discussed. Using Molinspiration software, the molecular properties of these compounds were calculated. These molecules are highly significant due to their extensive potential in medical applications. Salen and salophen, for instance, play crucial roles in cancer chemotherapy and act as inhibitors of angiogenesis. Curcumin is renowned for its antioxidant properties, …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 14–21 Read article
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Mathematical Modeling of Tumor Growth and Immune System Interaction Incorporating Time Delays and Suppression Effects for Tumor Control
Abstract: Cancer growth is a complex biological process influenced by various factors, including the dynamic interaction between tumor cells and the host immune system. Mathematical modeling serves as a powerful tool to understand these interactions and predict the outcomes of different therapeutic strategies. This study presents a mathematical framework that captures the essential dynamics of tumor-immune interactions, specifically incorporating the effects of time delay and immune suppression mechanisms. Time delay accounts …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 · pp. 25–34 Read article
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Critical Review on Multifunctional Polymer Composites for Weight Reduction and AI Based Battery Thermal Management in Electric Vehicles
Abstract: The rapid growth of electric vehicles (EVs) has intensified the need for advanced materials and intelligent control systems capable of improving energy efficiency, driving range, thermal safety, and overall vehicle sustainability. This paper presents a critical review of multifunctional polymer composites and artificial intelligence-based battery thermal management systems (AI-BTMS) for next-generation EV applications. Polymer composites reinforced with carbon fibers, graphene, boron nitride, nanoclays, and carbon nanotubes offer significant advantages over …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 603–619 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Design and Implementation of Low Power and High Speed 10T SRAM with High SNM
Abstract: The project introduces a low standby power 10T (LP10T) SRAM cell that focuses on achieving high read stability and write-ability while minimizing power consumption. The LP10T SRAM cell utilizes a strong cross-coupled structure that combines a standard inverter with a stacked transistor and a Schmitt-trigger inverter with a double-length pull-up transistor. One of the key advantages of the LP10T SRAM cell is that it separates the read path from the …
Published in Journal of Microcontroller Engineering and Applications · Vol. 10, Issue 1, 2023 · pp. 40–65 Read article
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A Reliable Low Standby Power 6T SRAM Cell
Abstract: The project introduces a low standby power 10T (LP10T) SRAM cell that focuses on achieving high read stability and write-ability while minimizing power consumption. The LP10T SRAM cell uses a robust cross-coupled design that combines a Schmitt-trigger inverter with a double-length pull-up transistor and a regular inverter with a stacking transistor. One of the key advantages of the LP10T SRAM cell is that it separates the read path from the …
Published in Journal of VLSI Design Tools and Technology · Vol. 13, Issue 1, 2023 · pp. 33–59 Read article
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Utility of Abbreviated Burn Scoring Index in Predicting Mortality in Burn Patients – Our Experience
Abstract: The prediction of the outcome of patients presenting with severe burns is crucial in guiding clinical judgments. There are multiple models for predicting burn mortality that have been developed over a period of time. Advancements in burn management over the past few decades have led to a remarkable reduction in burn-related morbidity and mortality worldwide. Improvements in critical care, fluid resuscitation protocols, infection control measures, nutritional support, early wound excision …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 2, 2026 · pp. 49–53 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Optimization of Machining Parameters for Minimum Surface Roughness Indicators during the Turning of AISI 316 L Stainless Steel
Abstract: Turning is the most common process associated with the production of cylindrical shapes because of its simplicity, rapidity and economy. However, it is one of the most complex cutting processes. Turning is considered to be a complementary process of other more important processes, and yet 70% of the generated chip comes from this cutting technique. Quality plays important role in manufacturing industry. In on-line quality control, controller is provided with …
Published in Journal of Mechatronics and Automation · Vol. 7, Issue 1, 2020 · pp. 24–30 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