In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...

This project explores retail chain performance in New Zealand by combining sales forecasting, regional sales analysis, and supply chain insights. Using real data and Python (including Prophet for ...

Time-series data—measurements collected at regular intervals, like stock prices or traffic flows—has become a key driver of intelligent decision-making systems across industries. From medical ...

Prediabetes increases a person's risk of developing Type 2 diabetes. An estimated 1 in 3 teens and preteens, ages 12 to 17, have prediabetes, according to new data from the Centers for Disease Control ...

Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain ...

Abstract: Data preprocessing is a crucial phase in the data science and machine learning pipeline, often demanding significant time and expertise. This step is vital for enhancing data quality by ...

Time-series data—measurements collected over time like stock prices or heart rates—plays a vital role in AI forecasting systems across industries. As these systems advance, the need for time-series ...