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503 articles for “predictive analysis”
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Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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A Random Forest Approach to Navigating Cryptocurrency Market Fluctuations
Abstract: This study looks at the main elements influencing daily price variations to improve our analysis and prediction of Bitcoin values. Our forecasting algorithm is based on comprehensive data that we have collected and analyzed over the last few years. Because the Random Forest algorithm provides more accurate forecasts than previous techniques, that is why we chose it. Predicting the price swings of cryptocurrencies, like Bitcoin, can be challenging due to …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 7–11 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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First Insights into Whole Genome Sequencing of the Mycobacterium tuberculosis Complex: Molecular Diversity and Drug Susceptibility Patterns in Senegal
Abstract: Background: We conducted a bibliographic analysis of the Mycobacterium tuberculosis complex (MTBC) in sub-Saharan Africa, which included the analysis of 8,139 genomic sequences from 34 of the 49 sub-Saharan African countries. Notably, only one complete sequence from Senegal was identified, which had been generated in the United States. Our primary objective was to utilize whole genome sequencing (WGS) to detect resistance in anti-tuberculous strains of the MTBC in Senegal. This …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 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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Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Enhancing Construction Safety Performance Through Artificial Intelligence: A Systematic Review
Abstract: The construction industry is still one of the most dangerous sectors globally because of its dynamic working environment, the employment of heavy machinery, and the complexity of operational processes. Traditional safety management methods are largely dependent on manual monitoring and reactive measures, which are not always effective for accident prevention. In recent years, Artificial Intelligence (AI) has been recognized as a revolutionary technology in construction safety, with capabilities such as …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 13–30 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Pharma Tech: Leveraging Software for Drug Development & Clinical Research
Abstract: The pharmaceutical sector is progressively adopting software solutions to enhance the drug development process and optimize clinical research results. Drug development is a time-consuming, expensive, and intricate process that traditionally requires extensive laboratory research, preclinical testing, and several stages of clinical trials. Software tools are revolutionizing these stages by improving efficiency, minimizing errors, and speeding up timelines. During preclinical testing, predictive software tools are used to model toxicological effects and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 11–19 Read article
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Detailed review on adsorption refrigeration system for different adsorbent/adsorbate working pair green composite materials – An environmental aspect
Abstract: Adsorption refrigeration is one of the greatest encouraging system for the refrigeration applications due to use of low grade energy. Present study deals with detailed review of adsorption refrigeration system. This article mainly concern with adsorption refrigeration arrangement by the utilization of most appropriate operational pairs namely activated carbon/methanol, silica gel/water and zeolite/water. Detail review carried out to predict thermal analysis and performance of the system. Mechanical properties of the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 1–9 Read article
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Navigating Risk-Based Approaches in Quality Assurance: Strategies, Implementation, and Impact
Abstract: This review investigates the implementation of a risk-based approach within Quality Management Systems (QMS) as stipulated by ISO 9001:2015 regulations. It scrutinizes the challenges organizations encounter when transitioning to ISO 9001-2015 requirements, particularly focusing on the alignment of conceptual frameworks and processes among stakeholders. A key objective of this review is to propose a refined definition of "quality risk" and "risk-based thinking in QMS" to address the idiosyncratic characteristics of …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 Read article
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Pharmacovigilance And Drug-Induced Toxicities: A Clinical Perspective
Abstract: Pharmacovigilance, which aims to detect, assess, and prevent medication-induced toxicities and adverse drug reactions (ADRs), is a crucial part of healthcare. This study examines the several kinds of drug-induced toxicities, such as idiosyncratic, dose-dependent, and allergic reactions, and emphasizes the function of clinical pharmacists in the tracking and treatment of these illnesses. Pharmacovigilance systems are crucial because they can identify and handle drug-related safety issues that might not surface during …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 3, 2024 · pp. 17–30 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article