In the present work we use text mining as a treatment tool for a large scientific database, with the aim of obtaining new information about all the publications signed by Argentine authors and indexed until 2019, in the area of life sciences. More than 75 000 articles were analysed, published in around 5000 media, signed by about 186 000 authors with a workplace in Argentina or in collaborations with Argentine laboratories. Using automated tools that were developed ad hoc, the text of around 70 800 abstracts was analysed, seeking, through non-supervised digital detection, the main topics addressed by the authors, and the relationship with health problems in Argentina and their treatment. Results are also presented regarding the number of publications per year, the journals that have published them, and their authors and collaborations. These results, together with the predictions that were obtained, could become a useful tool to optimize the management of resources dedicated to basic and clinical research.
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