Sáez Silvestre, Carlos; Gutiérrez-Sacristán, Alba; Kohane, Isaac; Garcia-Gomez, Juan M; Avillach, Paul(Oxford University Press, 2020-07-30)
[EN] Background: Temporal variability in health-care processes or protocols is intrinsic to medicine. Such variability can potentially introduce dataset shifts, a data quality issue when reusing electronic health records ...
Ferri-Borredà, Pablo; Romero-Garcia, Nekane; Badenes, Rafael; Lora-Pablos, David; García Morales, Teresa; Gómez de la Cámara, Agustín; Garcia-Gomez, Juan M.; Sáez Silvestre, Carlos(Elsevier, 2023-12)
[EN] Background and objective: Reusing Electronic Health Records (EHRs) for Machine Learning (ML) leads on many occasions to extremely incomplete and sparse tabular datasets, which can hinder the model development processes ...
Purpose
To develop a powerful archetype editing framework capable of handling multiple reference models and oriented towards the semantic description and standardization of legacy data.
Methods
The main prerequisite ...
Aerts, Hannelore; Kalra, Dipak; Sáez Silvestre, Carlos; Ramírez-Anguita, Juan Manuel; Mayer, Miguel-Angel; Garcia-Gomez, Juan M; Durá-Hernández, Marta; Thienpont, Geert; Coorevits, Pascal(JMIR Publications Inc., 2021-08)
[EN] Background: There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health ...