AIMC Topic: Artificial Intelligence

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Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases.

Methods in molecular biology (Clifton, N.J.)
The discovery and development of drugs is a long and expensive process with a high attrition rate. Computational drug discovery contributes to ligand discovery and optimization, by using models that describe the properties of ligands and their intera...

Artificial Intelligence in Compound Design.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence has seen an incredibly fast development in recent years. Many novel technologies for property prediction of drug molecules as well as for the design of novel molecules were introduced by different research groups. These artifi...

Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) consists of a synergistic assembly of enhanced optimization strategies with wide application in drug discovery and development, providing advanced tools for promoting cost-effectiveness throughout drug life cycle. Specifi...

Deep Learning Applied to Ligand-Based De Novo Drug Design.

Methods in molecular biology (Clifton, N.J.)
In the latest years, the application of deep generative models to suggest virtual compounds is becoming a new and powerful tool in drug discovery projects. The idea behind this review is to offer an updated view on de novo design approaches based on ...

De Novo Molecular Design with Chemical Language Models.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) offers new possibilities for hit and lead finding in medicinal chemistry. Several instances of AI have been used for prospective de novo drug design. Among these, chemical language models have been shown to perform well i...

Has Artificial Intelligence Impacted Drug Discovery?

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) tools find increasing application in drug discovery supporting every stage of the Design-Make-Test-Analyse (DMTA) cycle. The main focus of this chapter is the application in molecular generation with the aid of deep neura...

Application of Artificial Intelligence and Machine Learning in Drug Discovery.

Methods in molecular biology (Clifton, N.J.)
Machine Learning (ML) and Deep Learning (DL) are two subclasses of Artificial Intelligence (AI), that, in this day and age of big data provides significant opportunities to pharmaceutical discovery research and development by translating data to info...

Fighting COVID-19 with Artificial Intelligence.

Methods in molecular biology (Clifton, N.J.)
The development of vaccines for the treatment of COVID-19 is paving the way for new hope. Despite this, the risk of the virus mutating into a vaccine-resistant variant still persists. As a result, the demand of efficacious drugs to treat COVID-19 is ...

Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) has undergone rapid development in recent years and has been successfully applied to real-world problems such as drug design. In this chapter, we review recent applications of AI to problems in drug design including virtu...

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

Medical gas research
The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona-viruses that emerged in 2019 and spread rapidly around the world. The different symptoms of COVID-19 made it difficult to understand which variables ...