In an era characterized by an unprecedented influx of data, the skill to extract actionable
insights from this deluge has become paramount for organizations across diverse industries …

Data-Driven and Artificial Intelligence technologies are rapidly changing the way that health
research is conducted, including offering new opportunities. This will inevitably have …

Historically, low representation of women participants in exercise science and physiology
studies has led to a lack of understanding in the response of women to exercise and …

The increasingly sophisticated and rapidly evolving application of artificial intelligence in
medicine is transforming how health care is delivered, highlighting a need for current and …

Data Science is a field that has developed rapidly in recent years, which utilizes technology
and data analysis methods to produce useful information for various fields. In this paper, we …

Crowdsourced big data has faced growing criticism due to its quality issues, particularly
selection biases. We propose an interpretive framework for understanding selection biases …

Developing novel compositions of bioactive glasses (BGs) is key for accelerating tissue
repair and regeneration. In this work, we developed a series of cobalt (Co)-and copper (Cu) …

This research study explores the impact of machine learning and predictive analytics on
disease prevention in healthcare. By analyzing vast amounts of patient data, these …

This paper explores the integration of machine learning, specifically recurrent neural
networks (RNNs), for automated anomaly detection within NoSQL databases. It addresses …

Fraud detection in the fintech sector is a critical area of concern as financial transactions
increasingly shift to digital platforms. This paper presents a comprehensive analysis of …