Machine intelligence has the potential to play a significant role in diagnosing, managing, and guiding the treatment of disease, which supports the rising demands on healthcare to provide rapid and accurate interpretation of clinical data. The global pandemic caused by the Severe Acute...

This study demonstrates how convolutional neural networks (CNNs), supported by open-source software and guided by corporate social responsibility (CSR), can enhance photovoltaic (PV) panel maintenance. Connecting industrial informatics with sustainable practices underscores the potential for...

We propose a new machine-learning-based approach for forecasting Value-at-Risk (VaR) named CoFiE-NN where a neural network (NN) is combined with Cornish-Fisher expansions (CoFiE). CoFiE-NN can capture non-linear dynamics of high-order statistical moments thanks to the flexibility of a NN while...

In the feld of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction efects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting diferent measures of stock...