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11 articles for “Federated Analytics”
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Privacy-by-Design in Modern Data Science: A Systematic Review of Differential Privacy and Federated Analytics
Abstract: Okay so here is a problem that has been bothering us for a while. Everyone talks about how data is the new oil, how data-driven decisions are transforming healthcare, finance, governance, all of it. And that is true. But there is this massive elephant in the room that a lot of people in the data science community sort of wave away: privacy. The more useful the data, the more personal …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Federated Intelligence for Privacy-Preserving Health Data Analytics
Abstract: Healthcare artificial intelligence is limited by a structural conflict: useful models benefit from diverse multi-institutional data, while clinical records cannot be freely pooled because of privacy, ownership and governance constraints. This study presents a practical federated-learning framework for privacy-preserving health data analytics and validates its basic learning behavior in a reproducible cross-silo simulation. Five non-identical institutional clients were created from the public Breast Cancer Wisconsin (Diagnostic) dataset, and a standardized …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 3, 2026 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 Read article
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Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Drone Safety Protocols Developing and Implementing Safety Procedures
Abstract: The increasing utilization of drones across various sectors, including agriculture, logistics, surveillance, and recreational activities, necessitates the establishment of robust safety protocols to mitigate risks associated with their operation. This study explores the development and implementation of comprehensive safety procedures for drone operations, focusing on both regulatory compliance and technological advancements. The study emphasizes how crucial it is to comprehend the legal frameworks set forth by aviation authorities, including the …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 44–49 Read article
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Medical Image Processing Using Data Science: A Review
Abstract: The purpose of this work is to introduce data science in medical imaging. Both theoretical advancements and real-world applications are covered in this research work. The healthcare industry is distinct from all other industries and is a special sector. It is a top-priority industry that consumes a sizable percentage of the federal budget. In general, only doctors can analyses images, but thanks to technology, we are now able to use …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 7–15 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Smart HVAC Systems: The Role of IoT and AI in Energy Optimization
Abstract: Heating, ventilation, and air conditioning (HVAC) systems are crucial for maintaining interior comfort and air quality in all types of buildings. However, they also rank among the highest energy users in the built environment. Traditional HVAC systems are evolving into intelligent, networked systems through the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies, as energy efficiency and sustainability become increasingly important across the globe. This review article …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article