An exponential publication of research studies resulted in accumulation of academic information challenging the discovery of research information from literature search databases, journals, and search engines. Traditional literature search engines are based on keywords and controlled vocabulary rather than on concepts and words meaning. New generation literature search engines use Artificial Intelligence (AI), Machine Learning (ML), machine vision, semantic and textual analysis. These search engines use AI and semantic technologies to discover meaningful information for efficient access to knowledge in the heterogeneous informational environments. Semantic search engines use full-text indexing, smart filters, citation generation, exploration of the relevant concepts, creating search alerts, harvest articles in databases and the web, and ranking algorithms to understand the knowledge and information from abundant pools of radiological literature. The GoldMiner, Radiopedia, Yottalook, SearchingRadiology.com, Semantic Scholar, and Microsoft Academic are next generation search engines used for literature search in radiology, science, and medicine.
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