The intersection of artificial intelligence, genetic information, and health research presents complex ethical dilemmas that challenge existing data protection frameworks, including the European General Data Protection Regulation. This article examines the...
Machine Learning with Python (MLPY) has emerged as a cornerstone of modern data-driven research and intelligent system development. Python’s simplicity, extensive libraries, and strong community support make it one of the most widely adopted programming...
Artificial intelligence (AI) is an emerging technical field that employs computer technology to investigate and formulate the theories, methodologies, techniques, and application systems for the replication, enhancement, and augmentation of human...
Public-sector artificial intelligence can shape access to services, inspections, benefits, taxation, healthcare, mobility, and other consequential decisions. Its legitimacy therefore depends on more than predictive performance. Systems must avoid...
Governments worldwide recognize the increasing threats posed by cyberattacks on critical infrastructure, which encompasses sectors such as energy, healthcare, finance, and transportation. To mitigate risks and enhance resilience, national cybersecurity...
Cyber insurance and risk transfer mechanisms play a critical role in supporting public health entities' recovery in the aftermath of cyberattacks, which have become increasingly frequent and sophisticated. As public health organizations are highly dependent...
Large Language Models (LLMs) are rapidly transforming multiple sectors, including healthcare, finance, and cybersecurity, by enabling advanced data-driven insights and automation. However, the scale and complexity of LLMs introduce significant challenges in...
The rapid growth of data across scientific, industrial, and social domains has created an increasing demand for professionals skilled in data mining and knowledge discovery. This proposal presents a structured and comprehensive data mining curriculum...
Real-time data processing has emerged as a crucial tool for contemporary enterprises, allowing instantaneous analysis and response to perpetually created data. This study examines the significant influence of real-time data processing on corporate...
A lot of people across the world are talking about how AI and automation will affect the future of work, society, and the economy. We lay out the groundwork for artificial intelligence (AI) and big data (Big Data) and how they relate to public health in...
Contemporary Artificial Intelligence (AI) systems require fluid, scalable, and intelligent data streams to facilitate real-time analytics, model training, and automated decision-making. Traditional data pipelines are frequently inflexible, labour-intensive,...
Large Language Models (LLMs) such as GPT-3, GPT-4, BERT, and their domain-specific variants have rapidly transformed software development and a wide range of application domains, including healthcare, finance, e-commerce, travel, cybersecurity, and...
As the complexity of modern software systems continues to escalate, organizations face increasing pressure to enhance the efficiency, reliability, and speed of their software quality assurance (SQA) processes. In this dynamic and rapidly evolving landscape,...
Medical technologies driven by artificial intelligence are swiftly advancing into practical applications for clinical practice. Deep learning algorithms can manage the growing volumes of data generated by wearables, smartphones, and various mobile...
The use of artificial intelligence in critical infrastructure creates a new class of cyber-physical and institutional risks. AI systems depend on extensive data pipelines, complex models, software supply chains, cloud services, interfaces, and continuous...
In the era of digital transformation, organizations are increasingly reliant on cloud-centric data engineering frameworks to manage vast amounts of data efficiently. The exponential growth of data, coupled with its critical role in driving business...
As organizations increasingly leverage Artificial Intelligence (AI) to foster innovation and improve operational performance, the availability of high-quality, well-documented, and easily accessible data has become a decisive factor for success. This paper...
Various sectors within the healthcare industry have employed artificial intelligence (AI). The convergence of artificial intelligence and dentistry is captivating! Artificial intelligence (AI) has the capacity to completely transform several facets of...
The recent increase in the use of big data and analytics in various global industries has created pressure on industries to develop reliable and flexible frameworks for data governance. Historically used approaches can be ineffective in addressing the...
In the current digital landscape, characterized by the rapid expansion of Artificial Intelligence and data-intensive technologies, data governance has evolved into a strategic foundation for sustainable organizational growth rather than a purely regulatory...
Big data science has and is rapidly growing in the industries and is known to help in data analysis and forecasting. But the growth of data sharing in organizations creates many privacy problems especially in distributed environments. Discussing privacy...
Data quality is commonly understood as a technical challenge requiring measurement, validation, and correction of data errors. However, this perspective overlooks the fundamental socio-organizational dimensions that shape data quality outcomes. This review...
Recognition of images and voices, processing of natural languages, and even healthcare are just a few areas that have benefited greatly from the advent of machine learning and deep learning. Machine learning and deep learning are discussed in this article...
The rapid growth of Large Language Models (LLMs) has transformed multiple sectors, including healthcare, finance, cybersecurity, education, and supply chain management. As AI systems become increasingly integrated into critical decision-making processes,...
Distributed computing particularly, fault tolerant systems has indispensable functionality in maintaining the dependability and availability of the actual time applications across various sectors including but not limited to healthcare, aerospace,...
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