Núria
Correa
Industrial PhD Student
Learning Systems
Research areas:
- Causal Inference
- Machine Learning
- Optimisation
Impact areas:
- Healthcare
SDGs:
- GOAL 03: Good Health and Well-being
2024
Nuria Correa,
Jesus Cerquides,
Rita Vassena,
Mina Popovic,
& Josep Lluis Arcos
(2024).
IDoser: Improving Individualized Dosing Policies with Clinical Practice and Machine Learning.
Expert Systems with Applications, 238, 121796.
https://doi.org/10.1016/j.eswa.2023.121796.
[BibTeX]
[PDF]
Nuria Correa,
Jesus Cerquides,
Josep Lluis Arcos,
Rita Vassena,
& Mina Popovic
(2024).
Personalizing the First Dose of FSH for IVF/ICSI Patients through Machine Learning: A Non-Inferiority Study Protocol for a Multi-Center Randomized Controlled Trial.
Trials, 25, 38.
https://doi.org/10.1186/s13063-024-07907-2.
[BibTeX]
[PDF]
2023
N Correa Mañas,
J Cerquides,
J L Arcos,
R Vassena,
& M Popovic
(2023).
A clinically robust machine learning model for selecting the first FSH dose during controlled ovarian hyperstimulation: incorporating clinical knowledge to the learning process.
Human Reproduction, 38, dead093.226.
https://doi.org/10.1093/humrep/dead093.226.
[BibTeX]
[PDF]
2022
Nuria Correa,
Jesús Cerquides,
Josep Lluis Arcos,
& Rita Vassena
(2022).
Supporting first FSH dosage for ovarian stimulation with machine learning.
Reproductive Biomedicine Online.
https://doi.org/10.1016/j.rbmo.2022.06.010.
[BibTeX]
2021
Núria Correa,
Jesús Cerquides,
Josep Lluis Arcos,
& Rita Vassena
(2021).
Development and validation of an Artificial Intelligence algorithm that matches a clinician ability to select the best follitropin dose for ovarian stimulation.
Human Reproduction, 36.
https://doi.org/10.1093/humrep/deab130.636.
[BibTeX]
Núria Correa,
Rita Vassena,
Jesus Cerquides,
& Josep Lluis Arcos
(2021).
Limits of conventional Machine Learning methods to predict pregnancy and multiple pregnancy after embryo transfer.
Ada Valls, & Mateu Villaret (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 245-253).
IOS Press.
[BibTeX]