Abstract: The purpose of this study is to estimate and predict onion wholesale price volatility using statistical and machine learning algorithms. Traditional models like ARIMA and GARCH were compared ...

There is a version of the artificial intelligence story that some may say began with ChatGPT, or perhaps with the smartphone, ...

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.

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 ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

After apparently promising a climb back to $100,000 for about a week, Bitcoin (BTC) suddenly reversed late on Sunday, January 18, and ended up trading at $93,013 by press time on Monday. BTC price ...

XRP has lost some steam over the past twenty-four hours as the Senate delayed a key crypto market structure bill on January 15. At the same time, daily trading volume slipped 30% as the broader market ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer, with EGFR mutations serving as key oncogenic drivers. However, patients harboring EGFR mutations exhibit ...

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...