Publication: TopicTracker – An advanced software pipeline for text mining on PubMed data: Bridging the gap between off-the-shelf tools and code based approaches
TopicTracker – An advanced software pipeline for text mining on PubMed data: Bridging the gap between off-the-shelf tools and code based approaches
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Spitale, G., Germani, F., & Biller-Andorno, N. (2024). TopicTracker – An advanced software pipeline for text mining on PubMed data: Bridging the gap between off-the-shelf tools and code based approaches. Heliyon, 10(17), e36351. https://doi.org/10.1016/j.heliyon.2024.e36351
Abstract
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Background: The ever-increasing volume of academic literature necessitates efficient and sophisticated tools for researchers to analyze, interpret, and uncover trends. Traditional search methods, while valuable, often fail to capture the nuance and interconnectedness of vast research domains.
Results: TopicTracker, a novel software tool, addresses this gap by providing a comprehensive solution from querying PubMed databases to creating intricate semantic network maps. Through its functionalities, users can systematically search for d
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- Germani, Federico
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Spitale, G., Germani, F., & Biller-Andorno, N. (2024). TopicTracker – An advanced software pipeline for text mining on PubMed data: Bridging the gap between off-the-shelf tools and code based approaches. Heliyon, 10(17), e36351. https://doi.org/10.1016/j.heliyon.2024.e36351
