Drug development is expensive, time-consuming, and has a high failure rate. In recent
years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery …

Highlights•Artificial intelligence (AI) is transforming the drug discovery process by providing
actionable insights from huge amount of data.•Deep-learning models, especially generative …

There are two main ways to discover or design small drug molecules. The first involves fine-
tuning existing molecules or commercially successful drugs through quantitative structure …

Network management is a crucial task to maintain modern systems and applications
running. Some applications have become vital for society and are expected to have zero …

The utilization of large language models (LLMs) has become a significant advancement in
the domains of medicine and clinical informatics, providing a revolutionary potential for …

In recent years, generative machine learning algorithms have been successful in designing
innovative drug-like molecules. SMILES is a sequence-like language used in most effective …

Machine learning (ML) is revolutionizing drug repurposing, offering a more efficient, cost‐
effective approach to drug discovery by identifying new therapeutic uses for existing drugs …

Molecular docking is a vital computational method for predicting how small molecules bind
to target proteins, aiding drug discovery. It involves screening vast small molecule …

The integration of high-throughput genomic sequencing and advanced AI algorithms is
revolutionizing the fields of medicine and pharmaceuticals, particularly in the areas of …

Robust utility optimization enables an investor to deal with market uncertainty in a structured
way, with the goal of maximizing the worst-case outcome. In this work, we propose a …