Evolution of Artificial Intelligence-Powered Technologies in Biomedical Research and Healthcare.

Artificial intelligence represents a powerful computational tool to analyze large amounts of data with and without supervision. Such powerful techniques have significantly impacted the advancement of multiple sectors from social media to data security, the automotive industry, gaming, finances, and healthcare. Only recently, however, artificial intelligence has been making significant strides in healthcare and biomedical research. Despite such advancements and the expectation of potential breakthroughs arising from implementing artificial intelligence in these fields, there is limited knowledge transfer and training for most healthcare professionals on using these computational techniques. While there is a wide array of publications on artificial intelligence applied to scientific research, most are too technical (not aimed at the non-initiated), too broad (with an overwhelming amount of data), or too focused on a particular application. This chapter presents an overview of artificial intelligence and its derivatives, giving a historical perspective, a succinct technical explanation of the underlying basis, and some examples of its applications. It finishes with a brief discussion on the challenges for implementing AI to be fully accepted in the scientific community.

Machine-learning methods for ligand-protein molecular docking.

Artificial intelligence (AI) is often presented as a new Industrial Revolution. Many domains use AI, including molecular simulation for drug discovery. In this review, we provide an overview of ligand-protein molecular docking and how machine learning (ML), especially deep learning (DL), a subset of ML, is transforming the field by tackling the associated challenges.