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        (
            [journal] => stdClass Object
                (
                    [id_jnl] => 99
                )

        )

    [1] => stdClass Object
        (
            [section] => stdClass Object
                (
                    [section] => 1886
                )

        )

    [2] => stdClass Object
        (
            [title] => Array
                (
                    [0] => Natural Language Processing applied to anamnesis in the field of gynecology@en
                    [1] => Processamento de Linguagem Natural aplicado à anamneses do domínio da ginecologia@pt
                )

        )

    [3] => stdClass Object
        (
            [abstract] => Array
                (
                    [0] => The volume of information produced both in medical research and in clinical practice have required, since much time, the application of computational resources. An important source of real data, which is relevant for research, in addition to being essential for the management of health units, is the set of healthcare patient records of a hospital. Natural language processing (PLN) techniques consist of an important alternative to address this dynamic source in which new data is constantly recorded. The present research is conduct in this context, exhibiting an initiative to extract data from patient’s records in a large hospital using PLN techniques. To reach our goals, we present background information about such techniques, in adddition to methodological steps and partial results of the extraction conducted in the field of gynecology.@en
                    [1] => O volume de informação produzido tanto na pesquisa médica quanto na prática clínica há muito exige tratamento computacional. Uma importante fonte de dados reais, relevante para a pesquisa, além de essencial para a gestão das unidades de saúde, é o prontuário de paciente. Dessa forma, técnicas de processamento de linguagem natural (PLN) são alternativas importantes para lidar com essa fonte dinâmica onde constantemente se registram novos dados. A presente pesquisa se insere nesse contexto, exibindo uma iniciativa de extração de dados de pacientes em um grande hospital através de técnicas de PLN. Para tanto, apresenta-se um background com informações sobre tais técnicas para então descrever os passos metodológicos, bem como os resultados parciais da extração realizado no campo médico da ginecologia.@pt
                )

        )

    [4] => stdClass Object
        (
            [author] => Array
                (
                    [0] => Amanda  Damasceno de Souza
                    [1] => Eduardo Ribeiro Felipe
                )

        )

    [5] => stdClass Object
        (
            [subject] => Array
                (
                    [0] => Electronic health records@en
                    [1] => Medical history taking@en
                    [2] => Terminology@en
                    [3] => Natural language processing.@en
                )

        )

    [6] => stdClass Object
        (
            [source] => stdClass Object
                (
                    [vol] => 1
                    [nr] => 2
                    [year] => 2021
                    [theme] => 
                )

        )

    [7] => stdClass Object
        (
            [datePub] => Array
                (
                    [0] => 2021-12-27
                )

        )

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        (
            [DOI] => Array
                (
                )

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        (
            [http] => Array
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                    [0] => stdClass Object
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                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://periodicos.ufmg.br/index.php/advances-kr/article/view/37308
                                )

                        )

                    [1] => stdClass Object
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                            [type] => HTTP
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                                    [0] => https://periodicos.ufmg.br/index.php/advances-kr/article/view/37308/29321
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        )

    [10] => stdClass Object
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            [language] => Array
                (
                    [0] => en
                )

        )

    [11] => stdClass Object
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            [license] => Array
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                    [0] => Copr
                    [1] => CCBY4.0
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