In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Using routine clinical data, the model gauges liver cancer risk better than existing tools, offering a potential way to identify high-risk patients missed by current screening criteria.

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...