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Ivan Contreras
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Year
Artificial intelligence for diabetes management and decision support: literature review
I Contreras, J Vehi
Journal of medical Internet research 20 (5), e10775, 2018
6892018
Machine learning techniques for hypoglycemia prediction: trends and challenges
O Mujahid, I Contreras, J Vehi
Sensors 21 (2), 546, 2021
1072021
Prediction and prevention of hypoglycaemic events in type-1 diabetic patients using machine learning
J Vehí, I Contreras, S Oviedo, L Biagi, A Bertachi
Health informatics journal 26 (1), 703-718, 2020
1052020
Prediction of nocturnal hypoglycemia in adults with type 1 diabetes under multiple daily injections using continuous glucose monitoring and physical activity monitor
A Bertachi, C Viñals, L Biagi, I Contreras, J Vehí, I Conget, M Giménez
Sensors 20 (6), 1705, 2020
1002020
Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models
I Contreras, S Oviedo, M Vettoretti, R Visentin, J Vehí
PloS one 12 (11), e0187754, 2017
982017
Prediction of blood glucose levels and nocturnal hypoglycemia using physiological models and artificial neural networks.
A Bertachi, L Biagi, I Contreras, N Luo, J Vehí
KDH@ IJCAI, 85-90, 2018
902018
Risk-based postprandial hypoglycemia forecasting using supervised learning
S Oviedo, I Contreras, C Quirós, M Giménez, I Conget, J Vehi
International journal of medical informatics 126, 1-8, 2019
592019
Using grammatical evolution to generate short-term blood glucose prediction models.
I Contreras, A Bertachi, L Biagi, J Vehí, S Oviedo
KDH@ IJCAI, 91-96, 2018
392018
A machine learning approach to minimize nocturnal hypoglycemic events in type 1 diabetic patients under multiple doses of insulin
A Parcerisas, I Contreras, A Delecourt, A Bertachi, A Beneyto, I Conget, ...
Sensors 22 (4), 1665, 2022
362022
Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques
S Oviedo, I Contreras, A Bertachi, C Quirós, M Giménez, I Conget, J Vehi
Computer methods and programs in biomedicine 178, 175-180, 2019
342019
Generation of individualized synthetic data for augmentation of the type 1 diabetes data sets using deep learning models
J Noguer, I Contreras, O Mujahid, A Beneyto, J Vehi
Sensors 22 (13), 4944, 2022
292022
Impact of use frequency of a mobile diabetes management app on blood glucose control: evaluation study
J Vehi, JR Isern, A Parcerisas, R Calm, I Contreras
JMIR mHealth and uHealth 7 (3), e11933, 2019
292019
The effects of environmental factors on general human health: A scoping review
A Sundas, I Contreras, O Mujahid, A Beneyto, J Vehi
Healthcare 12 (21), 2123, 2024
272024
Matching island topologies to problem structure in parallel evolutionary algorithms
I Arnaldo, I Contreras, D Millán-Ruiz, JI Hidalgo, N Krasnogor
Soft Computing 17 (7), 1209-1225, 2013
272013
A GA combining technical and fundamental analysis for trading the stock market
I Contreras, JI Hidalgo, L Núñez-Letamendia
European Conference on the Applications of Evolutionary Computation, 174-183, 2012
272012
Profiling intra-patient type I diabetes behaviors
I Contreras, C Quirós, M Giménez, I Conget, J Vehi
Computer methods and programs in biomedicine 136, 131-141, 2016
252016
Artificial Intelligence in Precision Health: From Concept to Applications
D Barh
Elsevier - Academic Press, 2020
222020
Using a gpu-cpu architecture to speed up a ga-based real-time system for trading the stock market
I Contreras, Y Jiang, JI Hidalgo, L Núñez-Letamendia
Soft Computing 16 (2), 203-215, 2012
212012
The impact of missing continuous blood glucose samples on machine learning models for predicting postprandial hypoglycemia: An experimental analysis
NU Rehman, I Contreras, A Beneyto, J Vehi
Mathematics 12 (10), 1567, 2024
162024
Heart rate variability over the decades: a scoping review
A Sundas, I Contreras, J Navarro-Otano, J Soler, A Beneyto, J Vehi
PeerJ 13, e19347, 2025
142025
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Articles 1–20