This project aims to provide a collection of Python-based solutions for chemistry-related problems, ranging from data analysis and molecular visualization to predictive modeling using machine learning ...

The global community has faced substantial threats from infectious diseases in recent decades. As a crucial element of epidemic surveillance systems, infectious disease prediction technology plays an ...

World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel data often leads to ‘representation ...

do-mpc is a comprehensive open-source toolbox for robust model predictive control (MPC) and moving horizon estimation (MHE). do-mpc enables the efficient formulation and solution of control and ...

Functional connectivity (FC) analysis holds strong potential for predicting behavioral traits. However, whole-brain predictive models face challenges with interpretability and generalizability, while ...

Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the potential risks to patients and call for improved governance to ensure the ...

Dr. Bin Tang, Founder & CEO of Noah Digital, is an internationally recognized AI & digital marketing leader & author of “Local to Global.” For years, digital marketing has been synonymous with ...

Panelists discuss how clinical decision support tools, care pathways, and artificial intelligence can address primary care workforce shortages by providing real-time guidance, predictive modeling for ...

Gry Carl Terrell from the Danish Meat Research Institute introduces a valuable tool to maximise shelf life and ensure food safety A predictive model is a mathematical framework or algorithm that ...

Abstract: The future of agriculture depends on our ability to make informed, data-driven decisions about land use and crop management. This paper presents a comprehensive, humancentered approach to ...