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Drug Discovery Done Using AI

Artificial intelligence, particularly deep learning, has made significant progress in a variety of applications, including computer games, natural language processing, speech recognition, computer vision, driverless vehicles, automated interfaces for visual perception, decision making, and language translation, among others. AI hasn’t left any field unaffected. AI and robotics are no longer science fiction; they are altering healthcare, albeit a little late in comparison to other industries such as automobiles, gaming, marketing, and so on.

There is currently no competition for AI. Only AI (actionable insights) can be used for AI (artificial intelligence). AI is becoming increasingly capable of accomplishing what human experts do, but in a more competent, faster, and cost-effective manner. As a result, it is not an exaggeration to state that AI is transforming our daily lives. Recently, there has been a surge in interest in using AI and machine learning to find therapeutic compounds for a variety of ailments, as well as to forecast reactions and do retrosynthetic analyses, among other domain-specific applications.

Drug Discovery Done Using AIMedical imaging, Drug discovery, Drug repositioning, QA, marketing, sales, production, pharmaceutical analysis, and other departments of health businesses and institutions are all affected by AI. ML algorithms and DL models are two current AI methodologies. In 1959, IBM’s Arthur Samuel created the term ML, which has since become a buzzword.

Both AI and robotics have enormous potential in healthcare. AI and robotics are gradually becoming a part of our healthcare system, just like e-commerce websites or streaming platforms analyse our browsing and purchase history before delivering us highly customised info using various ML and DL models, just as they are in our everyday life.

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