RESEARCH
- Ahmad, S; Beneyto, A; Zhu, T; Contreras, I; Georgiou, P; Vehi, J An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems. Scientific Reports, 14, 15245. DOI
- Sundas, A; Contreras, I; Mujahid, O; Beneyto, A; Vehi, J The Effects of environmental Factors on General Human Health: A Scoping Review. Healthcare, 12 (21), 2123. DOI
- Noguer, J; Contreras, I; Beneyto, A; Vehi, J Modelling Rate of Exogeneous Glucose Appearance for Biomedical Applications Using Conditional Generative Models. IFAC-Papers Online, 58 (23), 127-132. DOI
- Ur Rehman, N; Conteras; I; Beneyto, A; Vehi, J The Impact of Missing Continuous Blood Glucose Samples on Machine Learning Models for Predicting Postprandial Hypoglycemia: An Experimental Analysis. Mathematics, 12(10), 1567. DOI
- Mujahid, O; Contreras, I; Beneyto, A; Vehi, J Generative deep learning for the development of a type 1 diabetes simulator. Communications Medicine, 4, 51. DOI
- Ibrahim, M.; Beneyto, A.; Contreras, I.; Vehi, J. An ensemble machine learning approach for the detection of unannounced meals in automated insulin delivery systems. Computers in Biology and Medicine, 171, 108154. DOI
- Estremera, E.; Beneyto, A.; Cabrera, A.; Contreras, I.; Vehí, J. Intermittent closed-loop blood glucose control for people with type 1 diabetes on multiple daily injections. Computer Methods and Programs in Biomedicine, 236, 107568. DOI
- Jacobs,P; Herrero,P; Facchinetti, A; Vehi, J;…Mosuqera-Lopez, C Artificial intelligence and machine learning for improving glycemic control in diabetes: best practices, pitfalls and opportunities. IEEE Review in Biomedical Engineering, 17, 19-41. DOI
- Muhammad, I; Beneyto, A; Contreras; Vehi, J Faults and Fault Tolerance In Automated Insulin Delivery Systems with an emphasis on human-in-the-loop. IFAC WC Japan, 56 (2), 11503-11514. DOI
- Contreras, I; Guso,M; Beneyto, A; Vehi,J Photo-based Carbohydrates counting using Pre-trained transformer models. IFAC WC Japan, 56 (2), 11533-11538. DOI
- Cabrera,A; Estremera,E; Beneyto, A; Biagi, L; Contreras, I; Martín-Fernandez, JA; Vehi, J Individualized Prediction of Blood Glucose Outcomes Using Compositional Data Analysis. Mathematics, 11(21), 4517. DOI
- Mesa, A; Beneyto, A; Martín-SanJose; Viaplana, J; Bondia, J; Vehi, J; Conget, I; Giménez, M Safety and performance of a hybrid closed-loop insulin delivery system with carbohydrate suggestion in adults with type 1 diabetes prone to hypoglycemia. Diabetes Research and Clinical Practice, 205, 110956. DOI
- Contreras, I; Navarro-Otano, J; Rodriguez-Pinto, I; Güemes, A; Alves, E; Rios-Garcés, R; Espinosa, G; Alehandre, A; Beneyto, A; Ramkisson, CM; Vehí, J; Cervera, R Optimizing Noninvasive Vagus Nerve Stimulation for Systemic Lupus Erythematosus: Protocol for a Multicenter Randomized Controlled Trial. JMIR Res Protoc, 12, e48387. DOI
- Contreras, I; Muñoz-Organero, M; Beneyto, A; Vehi, J Active labeling correction of mealtimes and the appearance of types of carbohydrates in type 1 diabetes information records. Mathematics, 11 (19), 4050. DOI
- Cabrera, A; Biagi, L; Beneyto, A; Estremera, E; Contreras, I; Gimenez, M; Conget, I; Bondia, J; Martín-Fernández, J.A; Vehi, J Validation of a Probabilistic Prediction Model for Patients with Type 1 Diabetes Using Compositional Data Analysis. Mathematics, 11(5), 1241. DOI
- Vehi, J; Mujahid, O; Contreras, I Aim and diabetes. Artificial Intelligence in Medicine. Springer, Cham., , 1-9. DOI
- Noguer, J; Contreras, I; Mujahid, O; Beneyto, A; Vehi, J Generation of Individualized Synthetic Data for Augmentation of the Type 1 Diabetes Data Sets Using Deep Learning Models. Sensors, 22(13), 4944. DOI
- Parcerisas,A; Contreras,I; Delecourt,A; Bertachi,A; Beneyto,A; Conget,I; Viñals,C; Giménez,M and Vehi,J A Machine Learning Approach to Minimize Nocturnal Hypoglycemic Events in Type 1 Diabetic Patients under Multiple Doses of Insulin. Sensors 2022, 22(4), 1665. DOI
- Vehi, J; Mujahid, O; Contreras, I, Artificial Artificial Intelligence and Machine Learning for Diabetes Decision Support. Advanced Bioscience and Biosystems for Detection and Management of Diabetes, , 259–272. DOI
- Estremera, E; Cabrera, A; Beneyto,A; Vehi, J A simulator with realistic and challenging scenarios for virtual T1D patients undergoing CSII and MDI therapy. Journal of Biomedical Informatics, 132, 104141. DOI
- Mujahid, O; Contreras, I; Beneyto, A; Conget,I; Gimenez, M; Vehi, J Conditional Synthesis of Blood Glucose Profiles for T1D Patients Using Deep Generative Models. Mathematics, 10(20), 3741. DOI
- Ahmad, S; Beneyto, A; Conteras, I; Vehi, J Bolus Insulin calculation without meal information. A reinforcement learning approach. Artificial Intelligence in Medicine, 134(1), 102436. DOI
- Contreras, I; Calm, R; Sainz, MA; Herrero, P: Vehi, J Combining Grammatical Evolution with Modal Interval Analysis: An Application to Solve Problems with Uncertainty. MATHEMATICS, 9 (6), 631. DOI
- Beneyto, A; Bequette, W; Vehi, J Fault-Tolerant Strategies for Automated Insulin Delivery Considering the Human Component: Current and Future Perspectives. Journal of diabetes science and technology, 15 (6), 1224-1231. DOI
- Mujahid, O; Contreras, I; Vehi, J Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges. SENSORS, 21 (2), 546. DOI
- Vinals, C; Beneyto, A; Martin-SanJose, JF; Furio-Novejarque, C; Bertachi,A; Bondia, Vehi, J; Conget, I; Gimenez, M Artificial Pancreas With Carbohydrate Suggestion Performance for Unannounced and Announced Exercise in Type 1 Diabetes. JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM, 106 (1), 55-63. DOI
- Toledo, EE; Vehi, J; Beneyto, A; Tejera, AC Generation Of Realistic Scenarios Including Insulin Variability and Mixed Meal Library. DIABETES TECHNOLOGY & THERAPEUTICS, 23, A97-A98. DOI
- M Flor, S Herraiz, I Contreras Definition of Residential Power Load Profiles Clusters Using Machine Learning and Spatial Analysis. Energies, 14 (20), 6565-6575. DOI
- Tejera, AC; Vehi, J; Beneyto, A; Toledo, EE Incorporating Long-Acting Insulin into The Hovorka Model for In Silico Simulations of Mdi Therapies in T1dm Patients. DIABETES TECHNOLOGY & THERAPEUTICS, 23, A98-A98. DOI
- Zainee, NM; Chellappan, K; Vehi, J ; Periyasamy, P The vital sign and haematological profile of adult dengue fever: a retrospective study. AIMS MEDICAL SCIENCE, 8 (1), 56-69. DOI
- Zainee, NM; Chellappan, K; Vehi, J ; Periyasamy, P; Man, ZC Clinical data analysis of dengue fever severity identification. BIOMEDICAL RESEARCH AND THERAPY, 8 (7), 4447-4455. DOI
- Beneyto, A;Puig, V; Bequette, BW;Vehi, J A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems. SENSORS, 21 (21), 7117. DOI
- Sainz, MA; Calm, R ;Jorba, L ;Contreras, I ;Vehi, J Marks: A New Interval Tool for Uncertainty, Vagueness and Indiscernibility. MATHEMATICS, 9 (17), 2116. DOI
- Ahmad, S;Ramkissoon, CM; Beneyto, A;Conget, I ;Gimenez, M; Vehi, J Generation of Virtual Patient Populations That Represent Real Type 1 Diabetes Cohorts. MATHEMATICS, 9 (11), 1200. DOI
- Biagi, L;Bertachi, A;Gimenez, M; Conget, I; Bondia, J; Martin-Fernandez, JA; Vehi, J Probabilistic Model of Transition between Categories of Glucose Profiles in Patients with Type 1 Diabetes Using a Compositional Data Analysis Approach. Sensors (Basel.), 21 (11), 3593. DOI
- Ramkinssoon, C; Guemes, A; Vehi,J Overview of therapeutic applications of non-invasive vagus nerve stimulation: a motivation for novel treatments for systemic lupus erythematosus. Bioelectronic medicine, 7 (1), 8. DOI
- Beneyto, A; Bertachi, A; Bondia, J; Vehi, J A New Blood Glucose Control Scheme for Unannounced Exercise in Type 1 Diabetic Subjects. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 28 (2), 593-600. DOI
- Bertachi, A; Vinals, C; Biagi, L; Contreras, I; Vehi, J; Conget, I; Gimenez, M Prediction of Nocturnal Hypoglycemia in Adults with Type 1 Diabetes under Multiple Daily Injections Using Continuous Glucose Monitoring and Physical Activity Monitor. Sensors, 20, 1705. DOI
- Vehi, J; Contreras, I; Oviedo, S; Biagi, L; Bertachi, A Prediction and prevention of hypoglycaemic events in type-1 diabetic patients using machine learning. HEALTH INFORMATICS JOURNAL, 26 (1), 703-718. DOI
- Bertachi, A; Biagi,L; Beneyto,A; vehi, J Dynamic Rule-Based Algorithm to Tune Insulin-on-Board Constraints for a Hybrid Artificial Pancreas System. JOURNAL OF HEALTHCARE ENGINEERING, , . DOI
- Vinals, C; Beneyto, A; Martin-Sanjose, JF; Furio-Novejarque, C; Bertachi, A; Bondia, J; Vehi, J; Conget, I; Gimenez,M Automatic Control of Blood Glucose Under Announced and Unannounced Exercise Using a New Multivariable Closed Loop Controller with Automatic Carbohydrate Suggestion and Mitigation Module. DIABETES TECHNOLOGY & THERAPEUTICS, 22, A36-A36. DOI
- Ramkissoon, CM; Bertachi, A; Beneyto, A; Bondia, J; Vehi, J Detection and Control of Unannounced Exercise in the Artificial Pancreas Without Additional Physiological Signals. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 24 (1), 259-267. DOI
- Contreras, I; Bertachi, A; Biagi, L; Oviedo, S;Ramkissoon, C; Vehi, J. Edited by Barh, D Chapter 14 – Artificial intelligence-based decision support systems for diabetes. ARTIFICIAL INTELLIGENCE IN PRECISION HEALTH: FROM CONCEPT TO APPLICATIONS, , 329-357 (Book Chapter). DOI
- Biagi, L; Bertachi, A; Quiros, C; Gimenez, M; Conget, I; Bondia, J; Vehi, J Accuracy of Continuous Glucose Monitoring before, during, and after Aerobic and Anaerobic Exercise in Patients with Type 1 Diabetes Mellitus. Diabetes Research and Clinical Practice, 8, e36-e39. DOI
- Ramkissoon, CM; Herrero, P; Bondia, J, Vehi, J Unannounced Meals in the Artificial Pancreas: Detection Using Continuous Glucose Monitoring. SENSORS, 18, . DOI
- Contreras,I; Oviedo, S; Vettoretti, M; Visentin, R; Vehi, J Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models. PLOS ONE, 12, . DOI
- Biagi, L; Bertachi, A; Conget,I; Quiros, C; Gimenez,M; Rosseti,P; Ampudia, FJ; Bondia,J; Vehí, J Extensive Assessment of Blood Glucose Monitoring During Postprandial Period and Its Impact on Closed-Loop Performance. Journal of diabetes science and technology, 11, 1089-1095. DOI
- Beneyto, A; Vehi, J Closed-loop blood glucose control using insulin and carbohydrates in front meals and exercise. IFAC PAPERSONLINE, 50, 2058-2063. DOI
- Ramkisson, C; Auferheide,B; Bequette, B; Vehi,J A Review of Safety and Hazards Associated With the Artificial Pancreas. IEEE Rev Biomed Eng, 10, 44-62. DOI
- Contreras, I; Hidalgo, JI; Nuñez, L; Velasco, JM A meta-grammatical evolutionary process for portfolio selection and trading. Genetic Programming and Evolvable Machines, 18, 411-431. DOI
- Oviedo,S; Contreras,I; Bertachi, A; Quiros, C ; Gimenez, M; Conget, I; Vehi, J Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 178, 175-180. DOI
- Oviedo, S; Contreras, I; Quiros, C; Gimenez, M; Conget, I; Vehi,J Risk-based postprandial hypoglycemia forecasting using supervised learning. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 126, 1-8. DOI
- Vehi, J; Isern, JR; Parcerisas, A; Calm, R; Contreras, I Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study. JMIR MHEALTH AND UHEALTH, 7 (3), e11933. DOI
- Bertachi, A; Ramkissoon, CM; Beneyto, A; Vehi, J Exercise-induced hypoglycemia in type 1 diabetes: in-silico comparison between announced and unannounced strategies in closed-loop control. IFAC PAPERSONLINE, 52, 1000-1005. DOI
- Biagi, L; Bertachi, A ; Martin-Fernandez, JA; Vehi, J Compositional Data Analysis of Glucose Profiles of Type 1 Diabetes Patients. IFAC PAPERSONLINE, 52, 1006-1011. DOI
- Bertachi, A; Viñals, C; Biagi, L; Contreras, I; Gimenez, M; Conget, I; Vehi, J Machine learning forecasting nocturnal hypoglycaemia in type 1 diabetes under multiple daily injections using continuous glucose monitoring and physical activity monitor. EASD Media Center, , . DOI
- Biagi, L; Bertachi, A; Gimenez, M; Conget, I; Bondia, J; Martin-Fernandez, JA; Vehi, J Categorization and Prediction of Glucose Profiles of Type 1 Diabetes Patients Based on a Compositional Data Analysis Approach. DIABETES TECHNOLOGY & THERAPEUTICS , 21, A70-A70. DOI
- Bondia, J; Vehi, J ;SanchezPena, RS; Chernavvsky, DR Strategies to mitigate hypoglycemia in the artificial pancreas. THE ARTIFICIAL PANCREAS: CURRENT SITUATION AND FUTURE DIRECTIONS, , 195-217. DOI
- Beneyto, A; Vehi, J Postprandial fuzzy adaptive strategy for a hybrid proportional derivative controller for the artificial pancreas. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 56, 1973-1986. DOI
- Quiros, C; Bertachi, A; Gimenez, M; Biagi, L ; Viaplana, J; Vinals, C; Vehi, J; Conget, I; Bondia, J Blood glucose monitoring during aerobic and anaerobic physical exercise using a new artificial pancreas system. ENDOCRINOLOGIA DIABETES Y NUTRICION, 65, 342-347. DOI
- Rosales, N; De Battista, H; Vehi, J; Garelli, F Open-loop glucose control: Automatic IOB-based super-bolus feature for commercial insulin pumps. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 159, 145-158. DOI
- Contreras,I; Vehi, J Artificial Intelligence for Diabetes Management and Decision Support: Literature Review. JOURNAL OF MEDICAL INTERNET RESEARCH, 20, . DOI
- Bertachi, A; Beneyto, A; Ramkissoon, CM; Vehi, J Assessment of Mitigation Methods to Reduce the Risk of Hypoglycemia for Announced Exercise in a Uni-hormonal Artificial Pancreas. DIABETES TECHNOLOGY & THERAPEUTICS 20, 20 (4), 285-295. DOI
- Quiros, C.; Bertachi, A.; Gimenez, M.; Biagi, L.; Viaplana, J.; Vinals, C.; Vehi, J.; Conget, I.; Bondia, J. Control de la glucemia durante el ejercicio físico aeróbico y anaeróbico mediante un nuevo sistema de páncreas artificial. Endocrinología, Diabetes y Nutrición, 65, 342-347. DOI
- Beneyto, A., Bertachi, A., Bondia, J., & Vehi, J. A new blood glucose control scheme for unannounced exercise in type 1 diabetic subjects. IEEE Transactions on Control Systems Technology, 28, 593-600. DOI
- Bertachi, A; Ramkissoon, CM; Bondia, J; Vehi, J Automated blood glucose control in type 1 diabetes: A review of progress and challenges. ENDOCRINOLOGIA DIABETES Y NUTRICION, 65, 172-181. DOI
- Vehi, J; Parcerisas, A; Calm, R; Regincos, J Mobile Diabetes Management App Significantly Reduces Low and High Blood Glucose Risks Regardless of Its Frequency of Use. DIABETES TECHNOLOGY & THERAPEUTICS, 20, A81-A82. DOI
- Contreras, I ;Hidalgo, J ;Nuñez, L Exploring The Influence Of Industries And Randomness In Stock Prices. Empirical Economics, 55(2), 713–729. DOI
- Biagi, L; Bertachi, A; Gimenez, M; Conget, I; Bondia, J; Martin-Fernandez, JA: Vehi, J Individual categorisation of glucose profiles using compositional data analysis. STATISTICAL METHODS IN MEDICAL RESEARCH, 28 (12), 3550-3567. DOI
- Liu, CY ; Vehi, J; Avari, P; Reddy, M; Oliver, N; Georgiou, P; Herrero, P Long-Term Glucose Forecasting Using a Physiological Model and Deconvolution of the Continuous Glucose Monitoring Signal. SENSORS, 19 (19), 4338. DOI