Artificial Intelligence (AI) is revolutionizing medical writing by enhancing the efficiency and
precision of healthcare communication and health research. This review explores the …

As organizations face the challenges of processing exponentially growing data volumes,
their reliance on analytics to unlock value from this data has intensified. However, the …

In this paper, we investigate Data Wrangling (DW) pipelines in the form of workflows devised
by data analysts with varying levels of experience to find commonalities or patterns. We …

Attention, or prioritization of certain information items over others, is a critical element of any
learning process, for both humans and machines. Given that humans continue to outperform …

During the 1990s and first decade of the 2000s, problem-solving environments (PSEs) were
a topic of research among a community with the vision to create software systems “with all of …

Many improvements to programming have come from shortening feedback loops, for
example with Integrated Development Environments, Unit Testing, Live Programming, and …

In the fast-evolving field of data science, the combination of the right team competencies has
a major impact on a successful project execution. These competencies, ranging from data …

The human-readable simplicity with which the CSV format was devised, together with the
absence of a standard that strictly defines this format, has allowed the proliferation of several …

Despite the rapid advancement of AI in various fields, there remains a gap in research
concerning its suitability and evaluation for general data analysis across diverse domains …

This thesis presents SLED (Semantic LLM Enrichment of Data), a Python library that
leverages Large Language Models (LLMs) to automate essential tasks in data wrangling …