News
| 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). |