| Automatic detection and prediction of cybersickness severity using deep neural networks from user’s physiological signals R Islam, Y Lee, M Jaloli, I Muhammad, D Zhu, P Rad, Y Huang, J Quarles 2020 IEEE international symposium on mixed and augmented reality (ISMAR …, 2020 | 58 | 2020 |
| Automatic detection of cybersickness from physiological signal in a virtual roller coaster simulation R Islam, Y Lee, M Jaloli, I Muhammad, D Zhu, J Quarles 2020 IEEE conference on virtual reality and 3D user interfaces abstracts and …, 2020 | 28 | 2020 |
| Implicit life event discovery from call transcripts using temporal input transformation network N Ebadi, B Lwowski, M Jaloli, P Rad IEEE Access 7, 172178-172189, 2019 | 23 | 2019 |
| Long-term prediction of blood glucose levels in type 1 diabetes using a cnn-lstm-based deep neural network M Jaloli, M Cescon Journal of diabetes science and technology 17 (6), 1590-1601, 2023 | 22 | 2023 |
| Estimating brain effective connectivity from EEG signals of patients with autism disorder and healthy individuals by reducing volume conduction effect F Salehi, M Jaloli, R Coben, AM Nasrabadi Cognitive Neurodynamics 16 (3), 519-529, 2022 | 10 | 2022 |
| A proposed algorithm for the detection of thyroid cancer based on image processing M Jaloli, M Fathi, SM Mohammadi, R Abbasi Kesbi Journal of Bioengineering Research 1 (3), 7-14, 2019 | 8 | 2019 |
| Incorporating the effect of behavioral states in multi-step ahead deep learning based multivariate predictors for blood glucose forecasting in type 1 diabetes M Jaloli, W Lipscomb, M Cescon BioMedInformatics 2 (4), 715-726, 2022 | 5 | 2022 |
| Predicting Blood Glucose Levels Using CNN-LSTM Neural Networks M Jaloli, M Cescon Diabetes Technology Meeting, 2020 | 4 | 2020 |
| Neurological Status Classification Using Convolutional Neural Network M Jaloli, D Choudhary, M Cescon IFAC-PapersOnLine 53 (5), 409-414, 2020 | 4 | 2020 |
| Basal-Bolus Advisor for Type 1 Diabetes (T1D) Patients Using Multi-Agent Reinforcement Learning (RL) Methodology M Jaloli, M Cescon arXiv preprint arXiv:2307.08897, 2023 | 1 | 2023 |
| Reinforcement Learning for Multiple Daily Injection (MDI) Therapy in Type 1 Diabetes (T1D) M Jaloli, M Cescon BioMedInformatics 3 (2), 422-433, 2023 | 1 | 2023 |
| System and method for predicting blood-glucose concentration M Cescon, M Jaloli US Patent App. 17/889,611, 2023 | 1 | 2023 |
| Demonstrating the Effect of Daily Physical Activities on Blood Glucose Level Variation in Type 1 Diabetes M Jaloli, M Cescon DIABETES TECHNOLOGY & THERAPEUTICS 24, A79-A79, 2022 | 1 | 2022 |
| Model Predictive Control (MPC) of an artificial pancreas with data-driven learning of multi-step-ahead blood glucose predictors EM Aiello, M Jaloli, M Cescon Control Engineering Practice 144, 105810, 2024 | | 2024 |
| Modeling Physical Activity Impact on Glucose Dynamics in People with Type 1 Diabetes for a Fully Automated Artificial Pancreas M Jaloli, M Cescon 2023 IEEE Conference on Control Technology and Applications (CCTA), 546-551, 2023 | | 2023 |
| Managing Blood Glucose Concentration in Type 1 Diabetes with Deep Learning-Based Methodologies M Jaloli | | 2023 |
| DEMONSTRATING THE EFFECT OF DAILY STRESS ON BLOOD GLUCOSE LEVEL VARIATION IN TYPE 1 DIABETES M Jaloli, M Cescon DIABETES TECHNOLOGY & THERAPEUTICS 24, A234-A234, 2022 | | 2022 |
| Characterising Sympathetic Response with Power Spectral Density Analysis D Choudhary, M Jaloli, M Cescon 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | | 2020 |
Marzia CesconUniversity of HoustonDirección de correo verificada de uh.edu
