Aplicaciones de inteligencia artificial para la gestión documental: experimentos, potencial y desafíos
DOI:
https://doi.org/10.26512/rici.v18.n1.2025.56534Palabras clave:
Inteligencia artificial, Gestión de documentos, Revisión bibliográfica, BibliometríaResumen
Desde 2022, con el lanzamiento de ChatGPT, la Inteligencia Artificial (IA) ha ganado notoriedad, popularidad y aplicación en diferentes sectores. La gestión documental (GD) se encuentra entre los dominios que pueden beneficiarse de esta solución computacional. En este contexto, este trabajo busca responder cómo se puede utilizar la IA para la gestión documental. El objetivo general es analizar la aplicabilidad de la Inteligencia Artificial para la Gestión Documental. Específicamente, buscamos identificar literatura científica que aborde la intersección entre IA y GD; identificar trabajos, autores y grupos relevantes para estudios que involucran IA y GD; identificar métodos, técnicas y aplicaciones de IA para la gestión de documentos; e, identificar referentes teóricos, perspectivas y tendencias de investigación. Para ello, adopta una perspectiva multimetodológica para revisar la literatura científica. Los procedimientos constan de cuatro fases. En el primero se realizó una búsqueda en Scopus, para el periodo de 2013 a 2023, con la cadena (“gestión documental” O “gestión de registros” O “gestión documental electrónica”) E “inteligencia artificial”. En la segunda fase, los datos recogidos en Scopus fueron analizados con la herramienta VosWiewer, con el fin de establecer un análisis cuantitativo y bibliométrico. En la tercera fase se leyeron los títulos, resúmenes y palabras clave de los artículos encontrados en Scopus y Consensus para seleccionar una bibliografía válida para el tema estudiado.
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Baron, J. R.; Payne, N. Dark archives and edemocracy: Strategies for overcoming access barriers to the public record archives of the future. Proceedings of the 7th International Conference for E-Democracy and Open Government, CeDEM 2017, 3–11, 2017. https://doi.org/10.1109/CeDEM.2017.27.
Bellucci, E.; Venkatraman, S.; Stranieri, A. Online dispute resolution in mediating EHR disputes: a case study on the impact of emotional intelligence. Behaviour and Information Technology, v. 39, n. 10, 1124–1139, 2020. https://doi.org/10.1080/0144929X.2019.1645209.
Belov, I. Automation of Electronic Document Management Systems Functions by Means of Artificial Intelligence Technologies. Herald of an Archivist, n. 1, 2017. https://doi.org/10.28995/2073-0101-2022-3-772-783.
Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L. Early temporal prediction of type 2 diabetes risk condition from a general practitioner electronic health record: a multiple instance boosting approach. Artificial Intelligence in Medicine, n. 105, 101847, 2020. https://doi.org/10.1016/j.artmed.2020.101847.
Bhatt, P. C.; Kumar, V.; Lu, T.-C. Identifying technology trends for blockchain applications in industry 4.0 domain: A patent perspective. 2021 IEEE International Conference on Social Sciences and Intelligent Management, SSIM 2021. https://doi.org/10.1109/SSIM49526.2021.9555213.
Borges Junior, E. A inteligência artificial seria mesmo artificial? Uma releitura do conceito de inteligência a partir das noções de extensão e de conectividade. Palabra Clave, v. 27, n. 1, e27111, 2024. https://doi.org/10.5294/pacla.2024.27.1.11.
Boudjemadi, R.; Jamila, M.; Lunn, J.; Aljumaili, W. The implementation of AI in health and medicine: Electronic Health Records Web based on integration of Logistic Regression Model for Diabetes Type 2 prediction. In 2021 14th International Conference on Developments in eSystems Engineering (DeSE) (p. 168-173). IEEE, 2021. https://doi.org/10.1109/DeSE54285.2021.9719368.
Buss, C.; Salm Junior, J. F.; Prado, J. M. K. do; Ardigo, J. D. A regulamentação no uso da Inteligência Artificial para o tratamento de dados no contexto da Ciência da Informação. Ciência da Informação em Revista, v. 11, e15315, 2024. https://doi.org/10.28998/cirev.2024v11e15315.
Cameron, S., Franks, P., & Hamidzadeh, B. Positioning Paradata: A Conceptual Frame for AI Processual Documentation in Archives and Recordkeeping Contexts. Journal on Computing and Cultural Heritage, v. 16, n. 4, 2023. https://doi.org/10.1145/3594728.
Caroprese, L.; Veltri, P.; Vocaturo, E.; Zumpano, E. Deep learning techniques for electronic health record analysis. 2018 9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018. https://doi.org/10.1109/IISA.2018.8633647.
Chigwada, J. P.; Tsvuura, G. Handbook of Research on Information and Records Management in the Fourth Industrial Revolution. In: Handbook of Research on Information and Records Management in the Fourth Industrial Revolution. 2021. https://doi.org/10.4018/978-1-7998-7740-0.
Dai, W.; Brisimi, T. S.; Adams, W. G.; Mela, T.; Saligrama, V.; Paschalidis, I. C. Prediction of hospitalization due to heart diseases by supervised learning methods. International Journal of Medical Informatics, v. 84, n. 3, p. 189-197, 2015. https://doi.org/10.1016/j.ijmedinf.2014.10.002.
Duan, Y; Edwards, J.; Dwivedi, Y. Artificial intelligence for decision making in the era of Big Data - evolution, challenges and research agenda. International Journal of Information Management, v. 48, p. 63-71, 2019. https://doi.org/10.1016/J.IJINFOMGT.2019.01.021.
Duell, J.; Fan, X.; Burnett, B.; Aarts, G.; Zhou, S.-M. A comparison of explanations given by explainable artificial intelligence methods on analyzing electronic health records. BHI 2021 - 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, Proceedings. 2021. https://doi.org/10.1109/BHI50953.2021.9508618.
Ferreira, F.; Gandomi, A.; Cardoso, R. Artificial Intelligence Applied to Stock Market Trading: A Review. IEEE Access, v. 9, p. 30898-30917, 2021. https://doi.org/10.1109/ACCESS.2021.3058133.
Fontoura, R. V; Villalobos, A. P. de O. Interfaces entre a Ciência da Informação e Inteligência Artificial: o uso de um chat inteligente. Ciência Da Informação Em Revista, v. 9, n. 1/3, p. 1–15, 2023. https://doi.org/10.28998/cirev.2022v9n1/3f.
Fountas, S.; Carli, G.; Sørensen, C. G.; Tsiropoulos, Z.; Cavalaris, C.; Vatsanidou, A.; Tisserye, B. A. Farm management information systems: Current situation and future perspectives. Computers and electronics in Agriculture, n. 115, p. 40-50, 2015. https://doi.org/10.1016/j.compag.2015.05.011.
Gayathri Hegde, M.; Shrishti Bekal, M.; Shenoy, P. D.; Venugopal, K. R. Preserving Privacy and Security of Electronic Health Records using Blockchain-based Federated Learning (BFL) Framework. IEEE Region 10 Humanitarian Technology Conference, R10-HTC, p. 853–859. 2023. https://doi.org/10.1109/R10-HTC57504.2023.10461823.
Gelashvili, T.; Pappel, I. Challenges of transition to paperless management: Readiness of incorporating AI in decision-making processes. 2021 8th International Conference on EDemocracy and EGovernment, ICEDEG 2021, p. 41–46. 2021. https://doi.org/10.1109/ICEDEG52154.2021.9530905.
Grechishcheva, S.; Efimov, E.; Metsker, O. Risk markers identification in EHR using natural language processing: hemorrhagic and ischemic stroke cases. Procedia Computer Science, n. 156, p. 142-149, 2019. https://doi.org/10.1016/j.procs.2019.08.189.
Groenner, L.; Faria, L.; Perissini, R; Gracioso, L. Um Estudo Bibliométrico sobre a pesquisa em Inteligência Artificial no Brasil. Brazilian Journal of Information Science: Research Trends, v. 16, e02147, 2022. https://doi.org/10.36311/1981-1640.2022.v16.e02147.
Guedes, V. L. S. A bibliometria e a gestão da informação e do conhecimento científico e tecnológico: uma revisão da literatura. Ponto de Acesso; v. 6, n. 2, 2012.
Hoffman, R. Using artificial intelligence to set information free. MIT Sloan Management Review, n. 58, p. 21-22, 2016. https://doi.org/10.7551/mitpress/11645.003.0007.
Hossain, E.; Rana, R.; Higgins, N.; Soar, J.; Barua, P. D.; Pisani, A. R.; Turner, K. Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review. Computers in Biology and Medicine, n. 155, 106649, 2023. https://doi.org/10.1016/j.compbiomed.2023.106649.
Houssein, E. H.; Mohamed, R. E.; Ali, A. A. Machine learning techniques for biomedical natural language processing: a comprehensive review. IEEE Access, n. 9, 140628-140653, 2021. https://doi.org/10.1109/ACCESS.2021.3119621.
Humphreys, L., Boella, G., van der Torre, L., Robaldo, L., di Caro, L., Ghanavati, S., & Muthuri, R. Populating legal ontologies using semantic role labeling. Artificial Intelligence and Law, v. 29, n. 2, p. 171–211, 2021. https://doi.org/10.1007/s10506-020-09271-3.
Jiang, F.; Jiang, Y.; Zhi, H.; Dong, Y.; Li, H.; Ma, S.; Wang, Y.; Dong, Q; Shen, H.; Wang, Y. Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, v. 2, p. 230 – 243, 2017. https://doi.org/10.1136/svn-2017-000101.
Kaplan, A.; Haenlein, M. Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, v. 62, n. 1, p. 15–25, 2019. https://doi.org/10.1016/J.BUSHOR.2018.08.004.
Kaufman, D. Desmistificando a inteligência artificial. Belo Horizonte: Autêntica, 2022.
Kurteva, K.; Tzanova, S. Electronic Document Management Systems in the Context of Scientific and Educational Project Management. Comparative Study and Discussion. 2023 32nd International Scientific Conference Electronics, ET 2023 - Proceedings. 2023. https://doi.org/10.1109/ET59121.2023.10279523.
Leaman, R.; Khare, R.; Lu, Z. Challenges in clinical natural language processing for automated disorder normalization. Journal of biomedical informatics, v. 57, p. 28-37, 2015. https://doi.org/10.1016/j.jbi.2015.07.010.
Leroy, G.; Gu, Y.; Pettygrove, S; Kurzius-Spencer, M. Automated lexicon and feature construction using word embedding and clustering for classification of ASD diagnoses using EHR. In Natural Language Processing and Information Systems: 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings 22 (p. 34-37). Springer International Publishing. 20017. https://doi.org/10.1007/978-3-319-59569-6_4.
Liu, J.; Liu, A.; Lu, X.; Welleck, S; West, P.; La Bras, R; Choi, Y.; Hajishirzi, H. Generated Knowledge Prompting for Commonsense Reasoning. arXiv preprint arXiv:2110.08387v3. 2022. https://doi.org/arXiv:2110.08387v3.
Ludermir, T. B. Inteligência Artificial e Aprendizado de Máquina: estado atual e tendências. Estudos Avançados, São Paulo, v. 35, n. 101, p. 85–94, 2021. https://doi.org/10.1590/s0103-4014.2021.35101.007.
Mello Filho, L. L. de; Araújo Júnior, R. H. Objetos de fronteira: um diálogo entre a ciência da informação e a ciência de dados. Encontros Bibli: Revista eletrônica de Biblioteconomia e Ciência da informação, v. 26, p. 1–22, 2021. https://doi.org/10.5007/1518-2924.2021.e77247.
Min, H. Artificial intelligence in supply chain management: theory and applications. International Journal of Logistics Research and Applications, v. 13, p. 13 – 39, 2010. https://doi.org/10.1080/13675560902736537.
Modiba, M. Legislation Used to Apply Artificial Intelligence for the Management of Records at the Council for Scientific and Industrial Research in South Africa. African Journal of Library Archives and Information Science, v. 32, n. 1, p. 21–35, 2022.
Modiba, M. Policy framework to apply artificial intelligence for the management of records at the Council for Scientific and Industrial Research. Collection and Curation, v. 42, n. 2, p. 53–60, 2023a. https://doi.org/10.1108/CC-11-2021-0034.
Modiba, M. User perception on the utilization of artificial intelligence for the management of records at the council for scientific and industrial research. Collection and Curation, v. 42, n. 3, p. 81–87, 2023b. https://doi.org/10.1108/CC-11-2021-0033.
Modiba, M.; Ngulube, P.; Marutha, N. Discharging Records Management Activities Using Artificial Intelligence at the Council for Scientific and Industrial Research, South Africa. African Journal of Library Archives and Information Science, v. 33, n. 1, p. 37–50, 2023c.
Negro-Calduch, E.; Azzopardi-Muscat, N.; Krishnamurthy, R. S.; Novillo-Ortiz, D. Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews. International journal of medical informatics, n. 152, 104507, 2021. https://doi.org/10.1016/j.ijmedinf.2021.104507.
Neves, B. C. Inteligência artificial e computação cognitiva em unidades de informação: conceitos e experiências. Logeion: Filosofia da Informação, v. 7, n. 1, p. 186-205, 2020. https://doi.org/10.21728/logeion.2020v7n1.p186-205.
Pan, Y.; Zhang, L. Roles of artificial intelligence in construction engineering and management: A critical review and future trends. Automation in Construction, n. 122, 103517, 2021. https://doi.org/10.1016/j.autcon.2020.103517.
Perianes-Rodriguez, A.; Waltman, L.; & Van Eck, N.J. Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, v. 10, n. 4, p. 1178-1195, 2016.
Pournader, M.; Ghaderi, H.; Hassanzadegan, A.; Fahimnia, B. Artificial intelligence applications in supply chain management. International Journal of Production Economics, n. 241, 108250, 2021. https://doi.org/10.1016/J.IJPE.2021.108250.
Rao, K. P. N.; Manvi, S. Survey on Electronic Health Record Management Using Amalgamation of Artificial Intelligence and Blockchain Technologies. Acta Informatica Pragensia, v. 12, n. 1, p. 179–199, 2023. https://doi.org/10.18267/j.aip.194.
Ravindar, K.; Gupta, M.; Abdul-Zahra, D. S.; Maiti, N.; Chawla, R.; Prashanth, K. S. Utilizing Nlp and Machine Learning To Predict Patient Outcomes From Electronic Health Records In Cloud Environments. International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023. https://doi.org/10.1109/ICAIIHI57871.2023.10489152.
Sampaio, R. C.; Lycarião, D. Análise de conteúdo categorial: manual de aplicação. Brasília: ENAP, 2021. Disponível em: https://repositorio.enap.gov.br/handle/1/6542. Acesso em: 3 jun. 2024.
Santaella, L. A inteligência artificial é inteligente? São Paulo: Almedina Brasil, 2023.
Secinaro, S.; Calandra, D.; Secinaro, A.; Muthurangu, V.; Biancone, P. The role of artificial intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21. 2021. https://doi.org/10.1186/s12911-021-01488-9.
Tella, A.; Olaniyi, O. T.; Dunmade, A. O. Records management in the fourth industrial revolution: Challenges and the way forward. In: Handbook of Research on Records and Information Management Strategies for Enhanced Knowledge Coordination. 2021. https://doi.org/10.4018/978-1-7998-6618-3.ch001.
Toorajipour, R.; Sohrabpour, V; Nazarpour, A.; Oghazi, P.; Fischl, M. Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, v. 122, p. 502-517, Jan. 2021. https://doi.org/10.1016/J.JBUSRES.2020.09.009
Torres E Silva, M. D., Carvalho, R. B., de Castro, J. M., & Soares, M. V. (2021). Information governance in the context of ERPsystems accounting modules for Industry 4.0: a framework proposal | Governança da informação no contexto dos módulos contábeis dos sistemas ERP para a Indústria 4.0: Proposta de framework. AtoZ: Novas práticas em informação E Conhecimento, v. 10, n. 3, p. 1–11, 2021. https://doi.org/10.5380/atoz.v10i3.81477
Turing, A. M. Computing machinery and intelligence. Springer Netherlands.
Viani, N., Patel, R., Stewart, R., Velupillai, S. (2019). Generating Positive Psychosis Symptom Keywords from Electronic Health Records. In: Riaño, D., Wilk, S., ten Teije, A. (eds) Artificial Intelligence in Medicine. AIME 2019. Lecture Notes in Computer Science, v. 11526. Springer, Cham., 2009. https://doi.org/10.1007/978-3-030-21642-9_38.
Vilar, S. B. Efficient Justice digital ecosystem (From Document-oriented digital Justice to Data-oriented Justice) | Ecosistema digital de Justicia eficiente (De la Justicia digital orientada al documento a la Justicia orientada al dato) (1) (2). Actualidad Civil, 5. 2023.
Villata, S.; Araszkiewicz, M.; Ashley, K.; Bench-Capon, T.; Branting, L. K.; Conrad, J. G.; Wyner, A. Thirty-years of artificial intelligence and law: the third decade. Artificial Intelligence and Law, v. 30, n. 4, p. 561–591, 2022. https://doi.org/10.1007/s10506-022-09327-6.
Wang, Y.; Wang, L.; Rastegar-Mojarad, M.; Moon, S.; Shen, F.; Afzal, N.; Liu, H. Clinical information extraction applications: a literature review. Journal of biomedical informatics, n. 77, p. 34-49, 2018a. https://doi.org/10.1016/j.jbi.2017.11.011.
Wang, Y.; Zhao, Y.; Therneau, T. M.; Atkinson, E. J.; Tafti, A. P.; Zhang, N.; Liu, H. Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records. Journal of biomedical informatics, n. 102, 103364, 2020. https://doi.org/10.1016/j.jbi.2019.103364.
Xie, S. L.; Gao, Y.; Han, R. Information Resilient Society in an AI World—Is XAI Sufficient? Proceedings of the Association for Information Science and Technology, v. 59, n. 1, p. 522–526, 2022. https://doi.org/10.1002/pra2.663.
Xie, S. L.; Siyi, L.; Han, R. Competing with artificial intelligence – can the records and information management profession withstand the challenge? Records Management Journal, v. 32, n. 2, p. 151–169, 2022. https://doi.org/10.1108/RMJ-08-2021-0033.
Zeng, Z.; Deng, Y.; Li, X.; Naumann, T.; Luo, Y. Natural language processing for EHR-based computational phenotyping. IEEE/ACM transactions on computational biology and bioinformatics, v. 16, n. 1, p. 139-153, 2019. https://doi.org/10.1109/TCBB.2018.2849968.
Zheng, T.; Xie, W.; Xu, L.; He, X.; Zhang, Y.; You, M.; Chen, Y. A machine learning-based framework to identify type 2 diabetes through electronic health records. International journal of medical informatics, n. 97, p. 120-127, 2017a. https://doi.org/10.1016/j.ijmedinf.2016.09.014.
Zheng, T.; Zhang, Y. A Big Data Application of Machine Learning-Based Framework to Identify Type 2 Diabetes Through Electronic Health Records. In: Uden, L., Lu, W., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2017. Communications in Computer and Information Science, v. 731, 2017b. Springer, Cham. https://doi.org/10.1007/978-3-319-62698-7_37.
Zong, N.; Wen, A.; Moon, S.; Fu, S.; Wang, L.; Zhao, Y.; Yu, Y.; Huang, M.; Wang, W.; Zheng, G.; Mielke, M. M.; Cerhan, J. R.; Liu, H. Computational drug repurposing based on electronic health records: a scoping review. npj Digit. Med., v. 5, 77, 2022. https://doi.org/10.1038/s41746-022-00617-6
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