Results: Integration of active and passive data outperformed single-modality models, achieving mean balanced accuracies of 0.71 for SDQ-high risk, 0.67 for insomnia, 0.77 for suicidal ideation, and ...

In the search for new drugs, artificial intelligence in the form of diffusion models is being used in drug design. What ...

Abstract: The introduction of Automated Machine Learning (AutoML) can be considered a game-changing development in the field of data science and more specifically, in the area of big data analytics.

Python has become the go-to language for data science thanks to its simplicity, flexibility, and massive library ecosystem. From data preprocessing to creating visualizations and building predictive ...

Python has become the go-to language for data science thanks to its simplicity, versatility, and massive library ecosystem. From cleaning messy datasets to building advanced machine learning models, ...

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...

This repo contains Python code to generate the global dataset of factor returns, stock returns, and firm characteristics from “Is there a Replication Crisis in Finance?” by Jensen, Kelly, and Pedersen ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...