Significance of the AI-NLP models for Oncological Text Databases of Electronic Health Records
Fancisco J. Veredas, Fernando Gallego, Guillermo LÃ³pez-GarcÃ­a,Nuria Ribelles, Emilio Alba and JosÃ© M. Jerez
International Journal of Computational Linguistics Research, Vol. 15, No. 3, 2024.
DOI: https://doi.org/10.6025/ijclr/2024/15/3/97-104
Link: https://www.dline.info/jcl/fulltext/v15n3/jclv15n3_1.pdf
Abstract:
The AI-NLP models developed under the Text2RWD initiative are not only enhancing the development and anonymization of a particular medical dataset, but also have the potential to be shared and utilized in other medical fields. These models are being customized for tasks involving the analysis of unstructured text data found in oncological electronic health records within GalÃ©n, a system for managing healthcare information. They will be evaluated and confirmed by being applied to various clinically relevant tasks using real-world data from oncology departments. The AI-NLP models are also projected to be shared and utilized in analysing text databases from other medical fields or healthcare environments to validate their effectiveness in extracting information and predicting outcomes in these specific domains.