Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Mohammed Benaissa

Showing results (11-20 of 35) with videos related to

Pageof 4
Sort By:
Bioengineering (Basel, Switzerland)|April 28, 2023
Blood Glucose Level Time Series Forecasting: Nested Deep Ensemble Learning Lag FusionHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Sensors (Basel, Switzerland)|November 26, 2022
Interpretable Machine Learning for Inpatient COVID-19 Mortality Risk Assessments: Diabetes Mellitus Exclusive InterplayHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Heliyon|May 23, 2024
In Vitro Glucose Measurement from NIR and MIR Spectroscopy: Comprehensive Benchmark of Machine Learning and Filtering ChemometricsHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Computers in Biology and Medicine|January 14, 2023
Causality analysis in type 1 diabetes mellitus with application to blood glucose level predictionHoda Nemat, Heydar Khadem, Jackie Elliott, et al.
Analytical Methods : Advancing Methods and Applications|September 10, 2021
Sammon's mapping regression for the quantitative analysis of glucose from both mid infrared and near infrared spectraKrishna Chaitanya Patchava, Shuzhi Sam Ge, Mohammed Benaissa
Journal of Personalized Medicine|April 27, 2026
Personalised Blood Glucose Time Series Forecasting in Type 1 Diabetes: Deep Collaborative Adversarial LearningHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Savitzky-Golay coupled with digital bandpass filtering as a pre-processing technique in the quantitative analysis of glucose from near infrared spectraKrishna Chaitanya Patchava, Osamah Alrezj, Mohammed Benaissa, et al.
IEEE Journal of Biomedical and Health Informatics|February 25, 2020
Intelligent Data-Driven Model for Diabetes Diurnal Patterns AnalysisMohammad R Eissa, Tim Good, Jackie Elliott, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 25, 2017
Coupling Scatter Correction with bandpass filtering for preprocessing in the quantitative analysis of glucose from near infrared spectraOsamah Abdulhameed Alrezj, Krishna Chaitanya Patchava, Mohammed Benaissa, et al.
Journal of Molecular Modeling|April 6, 2026
MGPP-DL: deep learning approach for material graph properties predictionOuthman Abbassi, Hicham Labrim, Soumia Ziti, et al.
Pageof 4

Showing results (11-20 of 35) with videos related to

Sort By:
Pageof 4
Bioengineering (Basel, Switzerland)|April 28, 2023
Blood Glucose Level Time Series Forecasting: Nested Deep Ensemble Learning Lag FusionHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Sensors (Basel, Switzerland)|November 26, 2022
Interpretable Machine Learning for Inpatient COVID-19 Mortality Risk Assessments: Diabetes Mellitus Exclusive InterplayHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Heliyon|May 23, 2024
In Vitro Glucose Measurement from NIR and MIR Spectroscopy: Comprehensive Benchmark of Machine Learning and Filtering ChemometricsHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Computers in Biology and Medicine|January 14, 2023
Causality analysis in type 1 diabetes mellitus with application to blood glucose level predictionHoda Nemat, Heydar Khadem, Jackie Elliott, et al.
Analytical Methods : Advancing Methods and Applications|September 10, 2021
Sammon's mapping regression for the quantitative analysis of glucose from both mid infrared and near infrared spectraKrishna Chaitanya Patchava, Shuzhi Sam Ge, Mohammed Benaissa
Journal of Personalized Medicine|April 27, 2026
Personalised Blood Glucose Time Series Forecasting in Type 1 Diabetes: Deep Collaborative Adversarial LearningHeydar Khadem, Hoda Nemat, Jackie Elliott, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|March 9, 2017
Savitzky-Golay coupled with digital bandpass filtering as a pre-processing technique in the quantitative analysis of glucose from near infrared spectraKrishna Chaitanya Patchava, Osamah Alrezj, Mohammed Benaissa, et al.
IEEE Journal of Biomedical and Health Informatics|February 25, 2020
Intelligent Data-Driven Model for Diabetes Diurnal Patterns AnalysisMohammad R Eissa, Tim Good, Jackie Elliott, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 25, 2017
Coupling Scatter Correction with bandpass filtering for preprocessing in the quantitative analysis of glucose from near infrared spectraOsamah Abdulhameed Alrezj, Krishna Chaitanya Patchava, Mohammed Benaissa, et al.
Journal of Molecular Modeling|April 6, 2026
MGPP-DL: deep learning approach for material graph properties predictionOuthman Abbassi, Hicham Labrim, Soumia Ziti, et al.
Pageof 4