ABSTRACT
The earlier traditional methods for screening chemicals for the purpose of scientific research were tediously time-consuming and often involved countless trials and errors. The advent of Artificial Intelligence (AI) changed things tremendously and led to a new era in the field of cheminformatics by improvising in silico studies. Currently, AI has gained dominance and its applicability is ever escalating and will continue to rise. This technology is still evolving and constantly being researched by the scientific community. AI caters to the need of many scientific domains such as bioinformatics, cheminformatics, forensic sciences, drug discoveries, etc. CNN (Convolutional Neural Network) falls under the various segments of AI that are employed for processing, screening, and interpreting an image. It is designed for the purpose of efficient recognition and highly accurate prediction of 2D or 3D images, videos, graphs, and structures. This chapter provides an overview of numerous facets of CNN-based AI and their performance in chemistry and biological fields of study. The chapter also sheds light on the fundamental mechanisms and industrial significance of the same. The current implementation and challenges concerned with this technology are also discussed. Then we conclude by looking into future perspectives and areas of visionary development.
