News

ATTD Conference
03/2024		 Valentina, Leah, and Peter present the work of the AIMS Lab on (1) physiology-guided AI digital twins in type 1 diabetes, (2) AI-based inference of meal insulin dosing behavior in people with type 1 diabetes, and (3) automated meal detection for closed loop at the 17th ATTD Conference in Florence, Italy.
New paper
11/2023
P. G. Jacobs et al., “Artificial intelligence and machine learning for improving glycemic control in diabetes: best practices, pitfalls and opportunities,” IEEE Rev. Biomed. Eng., pp. 1–19, 2023, doi: 10.1109/RBME.2023.3331297.
The DiabetesMine Innovation Summit
11/2023		 Clara presents the work of the AIMS Lab on automated meal detection for closed loop in San Diego, CA.
Virtual Diabetes Technology Meeting
11/2023		 Clara presents the work of the AIMS Lab on uncertainty-aware nocturnal hypoglycemia prediction.
New paper
10/2023
C. Mosquera-Lopez et al., “Combining uncertainty-aware predictive modeling and a bedtime Smart Snack intervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections,” Journal of the American Medical Informatics Association, p. ocad196, Oct. 2023, doi: 10.1093/jamia/ocad196.
New paper
09/2023
T. Kushner, C. Mosquera-Lopez, A. Hildebrand, M. H. Cameron, and P. G. Jacobs, “Risky movement: Assessing fall risk in people with multiple sclerosis with wearable sensors and beacon-based smart-home monitoring,” Multiple Sclerosis and Related Disorders, vol. 79, p. 105019, Nov. 2023, doi: 10.1016/j.msard.2023.105019.
New paper
03/2023
C. Mosquera-Lopez et al., “Enabling fully automated insulin delivery through meal detection and size estimation using Artificial Intelligence,” npj Digit. Med., vol. 6, no. 1, Art. no. 1, Mar. 2023, doi: 10.1038/s41746-023-00783-1.
New paper (Recognized as paper of the month by OHSU School of Medicine)
02/2023
C. Mosquera-Lopez, K. L. Ramsey, V. Roquemen-Echeverri, and P. G. Jacobs, “Modeling risk of hypoglycemia during and following physical activity in people with type 1 diabetes using explainable mixed-effects machine learning,” Computers in Biology and Medicine, vol. 155, p. 106670, Mar. 2023, doi: 10.1016/j.compbiomed.2023.106670.
New QSB award
02/2023		 The BE-In-AIMS internship program will be supported by the 2023 OHSU Quantitative and Systems Biology (QSB) award; with Dr. Jacobs
New award
12/2022		 Valentina Roquemen-Echeverri was awarded a Professional Development Scholarship from Women in Science Portland. Congratulations!
Colombian Endocrinology Association (ACE) DITEC 1.0 virtual course
10/2022		 Clara gave a talk on AI and its applications in diabetes management hosted by Dr. Alex Ramirez-Rincon
New JDRF award
09/2022		 "Development of an open-source AI-based digital twin generator for replicating personalized glucose dynamics in people with type 1 and type 2 diabetes"; with AIMS Lab team
New paper
08/2022
J. R. Castle et al., “Assessment of a Decision Support System for Adults with Type 1 Diabetes on Multiple Daily Insulin Injections,” Diabetes Technology & Therapeutics, Aug. 2022, doi: 10.1089/dia.2022.0252.
ATTD Conference
04/2022		 Clara presents the work of the AIMS Lab on (1) automated meal detection for closed loop and (2) hypoglycemia risk during and following physical activity at the 15th ATTD Conference in Barcelona, Spain.
New student
03/2022		 Valentina Roquemen-Echeverri joins the AIMS Lab. Welcome Valentina!
New paper
03/2022
N. S. Tyler, C. Mosquera-Lopez, G. M. Young, J. El Youssef, J. R. Castle, and P. G. Jacobs, “Quantifying the impact of physical activity on future glucose trends using machine learning,” iScience, vol. 25, no. 3, p. 103888, Mar. 2022, doi: 10.1016/j.isci.2022.103888.
New OHSU REI + BME award
11/2021		 "Bias Equity and Inclusion in Artificial Intelligence for Medical Systems Internship (BE-In-AIMS)"; with Dr. Jacobs
Oregon Bioengineering Symp.
11/2021		 Clara gives a presentation on some of the work in the AIMS Lab.
New OCTRI IDEA Gap award
 "Development of a Novel Smart-Phone-Based Stethoscope Device that uses Machine Learning to Detect, Diagnose, and Determine the Severity of Cardiac and Pulmonary Disease"; with Dr. Schulman, Dr. Heitner, and Dr. Jacobs
New NIH/NIDDK R21 award
09/2021		 "Development and Evaluation of Personalized Explainable Machine Learning Models to Predict and Prevent Nocturnal Hypoglycemia in Type 1 Diabetes"; with AIMS Lab team
New paper
09/2021
C. Mosquera-Lopez and P. G. Jacobs, “Incorporating Glucose Variability into Glucose Forecasting Accuracy Assessment Using the New Glucose Variability Impact Index and the Prediction Consistency Index: An LSTM Case Example,” J Diabetes Sci Technol, vol. 16, no. 1, pp. 7–18, Jan. 2022, doi: 10.1177/19322968211042621.
New MRF award
03/2021		 Clara Mosquera-Lopez and the team in the AIMS Lab were awarded a New Investigator grant from the Medical Research Foundation to study the effect of different forms of exercise on hypoglycemia risk in people with Type 1 Diabetes and to develop exercise-aware machine learning models for accurate prediction of short- and long-term hypoglycemia (including overnight hypoglycemia).