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344 articles for “Gene prediction”
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 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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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Smart Weather Monitoring and Forecasting System Using Machine Learning (ML)
Abstract: The Smart Weather Monitoring System & Forecasting using Machine Learning (ML) represents an innovative approach to modern weather prediction and monitoring. This system combines the capabilities of machine learning algorithms with vast sets of weather data to provide accurate and timely weather forecasts. By collecting and analyzing data points like temperature, humidity, light intensity, rainfall, and atmospheric pressure, the system can generate precise predictions for a wide range of applications. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 1, 2024 · pp. 12–21 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 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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Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Novel Strategic Framework for AI-Driven Discovery and Development of Smart and Sustainable Polymers in Healthcare
Abstract: The development of new smart and sustainable polymers is emerging as a priority of new health care innovative development, but event before it may be actualized, the usual culprit is the delay and unproductive execution of the old-fashioned R&D efforts. The current paper proposes a strategic plan which will solve all these shortcomings and speed up the material discovery process by using Artificial Intelligence (AI) and Machine Learning (ML). The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1535–1550 Read article
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Gravitational Wave Astronomy (2015–2026): From Historic Discoveries to Quantum Detection Frontiers
Abstract: Since the landmark detection of GW150914 by the LIGO Scientific Collaboration in 2015, gravitational wave (GW) astronomy has transitioned from a theoretical frontier to a robust observational science. This breakthrough confirmed a major prediction of General Relativity and inaugurated an entirely new method for observing the universe. Over the past decade, continuous upgrades to ground-based interferometers such as LIGO, Virgo Collaboration, and KAGRA have dramatically improved detector sensitivity, enabling the …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 1–5 Read article
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Sequence analysis, DNA Methylation and Molecular therapy of Oral cancer caused by Human Papilloma Virus
Abstract: DNA methylations with oral cancer are been associated with high-risk Human Papillomavirus (HPV) and Epstein-Barr Virus (EBV) onco-proteins interactions may cooperate to increase disease severity. The work focused on human papillomavirus strain 16, a high-risk, sexually transmitted responsible for 95% of all cervical cancers and a large portion of oropharyngeal cancers. The prediction of genes from has shown seven genes from HPV16 strain. Based on gene identification studies, Human papilloma …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 · pp. 1–9 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Study on the Method of Prediction of Complete Inflation Time of Parachute
Abstract: In general, the parachute test is a long test period, expensive, and difficult to measure with accuracy, which makes it a very laborious and laborious task due to the strong nonlinearity of the fabric of the parachute. Therefore, attempts have been made to overcome this by using a parachute testbed or by simulation, but in our country, there is no numerical simulation of the parachute, and no research has been …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 25–31 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Prediction of Molecular Targets for Anthraquinone and Its Analogs for Treatment of Good Pasteur Syndrome
Abstract: Objective: In order to find prospective molecular targets for the treatment of Good Pasteur Syndrome (GPS), a rare autoimmune disease that affects the kidneys and other organs, computational methods and network pharmacology were applied in this work. The goal of the study is to identify particular human proteins that might interact with anthraquinone and its analogues as well as to uncover potential mechanisms of action by which these drugs might …
Published in International Journal of Bioinformatics and Computational Biology Read article
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Data-Driven Digital Twin Model for Real-Time Strength Estimation in Polymeric Materials
Abstract: The real-time prediction of mechanical properties in polymeric materials is essential for ensuring quality, consistency, and operational efficiency in modern manufacturing systems. As industrial processes become increasingly complex, traditional trial-and-error approaches to material characterization are no longer sufficient to meet the demands of high-throughput production environments. This study introduces a digital twin-integrated machine learning approach for the real-time estimation of tensile strength in polymeric materials by combining simulation-driven insights with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 246–257 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article