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543 articles for “predictive algorithm”
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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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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Integrating Sensor Technologies and Machine Learning for Detection and Mitigation of Structural Deformity and Slope Failure in Opencast Mines
Abstract: With furtherance in the mining industry, accidents due to slope failure are frequent in mining sites. Slope instability, a complex process, seriously threatens the miner’s life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research aims to develop an innovative approach that combines sensor technologies and machine learning techniques to detect and mitigate …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 3, 2023 · pp. 38–45 Read article
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Prediction of Disease by Symptoms Using Machine Learning
Abstract: Machine Learning and data mining, both play the most popular role in analyzing and prediction in the field of health organization. It also helps to uncover different and new patterns in medicinal science. This project is around prediction of disease with help of the symptoms. This project aims to propose a model which will be strongly trained in detecting common diseases so that few of the common diseases can be …
Published in Journal of Advancements in Robotics · Vol. 9, Issue 1, 2022 · pp. 8–11 Read article
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Sensorless Direct Power Control of Brushless DC Motor Drive using Unknown Input Speed Observer
Abstract: This paper proposes the speed control of brushless DC (BLDC) motor via direct power control (DPC) method as a novel and effective strategy in electrical drives applications. The DPC has some advantages rather than other control methods of BLDC motor including simpler control algorithm and faster dynamic response. In proposed BLDC motor drive based on DPC strategy, space vector modulation (SVM) voltage source inverter is employed. To enhance the drive …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 31–41 Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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Transforming Punjab's Education System: A Critical Analysis of Automation and Artificial Intelligence
Abstract: The rapid advancement of Artificial Intelligence (AI) and automation technologies is transforming education systems across the globe. In Punjab, one of India's leading educational regions, AI-driven tools and automated technologies are increasingly being adopted to improve teaching, learning, assessment, administration, and institutional management. This study critically examines the impact of AI and automation on Punjab's education system by exploring their opportunities, challenges, and future prospects. The research is based on …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 31–42 Read article
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Artificial Intelligence–Driven Decision Support Systems for Smart and Efficient Data Analysis
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology reshaping the way organizations process information, analyze data, and support decision-making. With the rapid growth of digital data across sectors, traditional analytical methods often face limitations in handling large, complex, and dynamic datasets. AI-based techniques, particularly machine learning and intelligent decision support systems, provide advanced capabilities for identifying hidden patterns, predicting outcomes, and assisting in data-driven decisions. This paper examines the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Shock Response Spectrum and Its Damage Potential: An Application to Launch Vehicle Structures
Abstract: The present work briefly summarizes the analysis of pyrotechnic shocks encountered in launch vehicle structures using the shock response spectrum (SRS) and the pseudo velocity shock response spectrum techniques. The mathematical idealization assumes a single degree of freedom (SDOF) system model with base excitation. The mounting elements of SDOF system are assumed to be flexible and each mounting element can be described by its stiffness and damping parameters. The convolution …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 1, Issue 1-3, 2012 · pp. 67–80 Read article
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Exploring Artificial Intelligence in the Finance Sector
Abstract: Artificial intelligence (AI), machine learning (ML), and progressive algorithms illustrate a substantial technological leap with wide applications across sectors like automobiles, healthcare, gaming, finance, entertainment, and more. The foremost objective of AI is to produce intelligent, independent systems capable of self-sustaining decision-making. This study delivers a concise summary of AI, concentrating on its transformative influence on finance, especially within banking, asset firms, derivatives markets, and insurance enterprises. It summarizes the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 16–23 Read article
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Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Exploring Artificial Intelligence in Operating Systems for Consumer Enhanced Experience: Knowledge-Based Interfaces for Intelligent User Experience and System Optimization
Abstract: The convergence of knowledge-based systems, machine learning algorithms, and natural language interfaces that provide dynamic and context-sensitive behavior is another foundation for this change. AI-based operating systems are important because they can enhance user experiences via automation, self-optimization, and customization. AI signifies a new era of cognitive computing, from adaptive power management for desktops and embedded systems to predictive text and voice recognition on mobile devices. Furthermore, this ability to …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 26–30 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article
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Geographical Knowledge report on Agriculture by Spatial Data Mining
Abstract: Spatial Data Mining is nothing but the integration of Geographical Information System and Data Mining. The main objective of the present study i.e., Spatial Data Mining for Agriculture is to find or identify the potentially useful and ultimately understandable patterns in data which will be visualized on the map. Data Mining Algorithms such as clustering, classification, and association rules etc are applied for the Past and Future trends visualization for …
Published in Journal of Advanced Database Management & Systems · Vol. 5, Issue 1, 2018 · pp. 8–19 Read article
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Revolutionizing Software Engineering: Harnessing AI-driven Continuous Integration for Seamless Collaboration and Rapid Development
Abstract: In the dynamic landscape of software engineering, this paper introduces a revolutionary approach by integrating artificial intelligence (AI) into continuous integration processes. The research aims to redefine software development methodologies, leveraging AI-driven continuous integration (AI-CI) to enhance collaboration among development teams and accelerate software development cycles. The comprehensive study delves into the theoretical foundations and practical implications of AI-CI. The integration involves infusing AI algorithms into the continuous integration pipeline, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 3, 2023 · pp. 45–60 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Deploying Optimal Number of Sensors and Damage Detection in Structural Health Monitoring Using SEM-GA Method
Abstract: Detecting damages is the most important criterion in any engineering creation—be it a machine or a building. Among the engineering creation, civil engineering structures need a continuous monitoring to check their operations, performance and the health status of the structures. Damage detection cannot be done manually every time. Automated systems have to be developed in order to monitor the health of the structure periodically. Hence, structural health monitoring (SHM) aims …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 28–35 Read article