This month another segment of a series of live webinars is addressing the application and impact of artificial intelligence (AI) and other emerging technologies in the world of pharmacology. This interesting news about emerging technologies came to us from Pulmonary Vascular Research Institute (PVRI) in their article, “Machine learning and artificial intelligence approaches for PH: From screening to novel drug targets.”
Drug discovery and development is a complicated and a time and resource consuming process. Various computational approaches are regularly being developed to improve it. Modern methods include data mining, structure modeling, traditional machine learning and deep learning.
Modern biology has entered the era of big data, where data sets are too large, high-dimensional and complex for classical computational biology methods. The ability to learn at the higher levels of abstraction made deep learning a promising and effective tool for working with biological and chemical data.
Regardless of the nature of their business, most organizations have little knowledge on how emerging technologies create the results they do. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases.
Melody K. Smith
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
