Patient medical records contain several types of data, such as images, signals, or textual data. The integration of such data on a single system provides the possibility to select the clinical data of interest and then to choose the information extraction operation to be performed on such data. Formulating diagnoses of complex diseases is a challenging task, which is often the key to the precise identification of the correct therapies. Hence, a uniforming environment for data clinical staging, in which physicians can perform data annotations and images manipulation could be of great help in order to convey relevant information forming the clinical summary of a patient with great precision and detail. In this work we present a semi-automatic tool for clinical data annotation aiming to be a decision support system.
A framework for clinical data integration and annotation for decision support
Vizza P.;Tradigo G.;
2021-01-01
Abstract
Patient medical records contain several types of data, such as images, signals, or textual data. The integration of such data on a single system provides the possibility to select the clinical data of interest and then to choose the information extraction operation to be performed on such data. Formulating diagnoses of complex diseases is a challenging task, which is often the key to the precise identification of the correct therapies. Hence, a uniforming environment for data clinical staging, in which physicians can perform data annotations and images manipulation could be of great help in order to convey relevant information forming the clinical summary of a patient with great precision and detail. In this work we present a semi-automatic tool for clinical data annotation aiming to be a decision support system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
