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Sunil Belur Nagaraj

Showing results (1-10 of 13) with videos related to

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Computer Methods and Programs in Biomedicine|October 6, 2021
Kidney Age Index (KAI): A novel age-related biomarker to estimate kidney function in patients with diabetic kidney disease using machine learningSunil Belur Nagaraj, Lyanne M Kieneker, Michelle J Pena
Diabetes/Metabolism Research and Reviews|December 8, 2020
Identifying patients at increased risk of hypoglycaemia in primary care: Development of a machine learning-based screening toolStijn Crutzen, Sunil Belur Nagaraj, Katja Taxis, et al.
Diabetes, Obesity & Metabolism|August 27, 2020
Machine-learning-based early prediction of end-stage renal disease in patients with diabetic kidney disease using clinical trials dataSunil Belur Nagaraj, Michelle J Pena, Wenjun Ju, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
A novel dictionary for neonatal EEG seizure detection using atomic decompositionSunil Belur Nagaraj, Nathan Stevenson, William Marnane, et al.
Artificial Intelligence in Medicine|April 20, 2021
STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoringShreyasi Pathak, Changqing Lu, Sunil Belur Nagaraj, et al.
IEEE Transactions on Bio-Medical Engineering|October 21, 2014
Neonatal seizure detection using atomic decomposition with a novel dictionarySunil Belur Nagaraj, Nathan J Stevenson, William P Marnane, et al.
The American Journal of Emergency Medicine|September 30, 2025
Early sepsis prediction in the emergency department using machine learningRaymond J van Wijk, Sunil Belur Nagaraj, Jan C Ter Maaten, et al.
Anesthesia and Analgesia|April 15, 2020
Predicting Deep Hypnotic State From Sleep Brain Rhythms Using Deep Learning: A Data-Repurposing ApproachSunil Belur Nagaraj, Sowmya M Ramaswamy, Maud A S Weerink, et al.
Cancers|June 2, 2021
A Classification Approach for Cancer Survivors from Those Cancer-Free, Based on Health Behaviors: Analysis of the Lifelines CohortFrancisco O Cortés-Ibañez, Sunil Belur Nagaraj, Ludo Cornelissen, et al.
BMJ Health & Care Informatics|September 15, 2025
Automated sepsis prediction from unstructured electronic health records using natural language processing: a retrospective cohort studyLipi Mishra, Sowmya Muchukunte Ramaswamy, Broderick Ivan McCallum-Hee, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Computer Methods and Programs in Biomedicine|October 6, 2021
Kidney Age Index (KAI): A novel age-related biomarker to estimate kidney function in patients with diabetic kidney disease using machine learningSunil Belur Nagaraj, Lyanne M Kieneker, Michelle J Pena
Diabetes/Metabolism Research and Reviews|December 8, 2020
Identifying patients at increased risk of hypoglycaemia in primary care: Development of a machine learning-based screening toolStijn Crutzen, Sunil Belur Nagaraj, Katja Taxis, et al.
Diabetes, Obesity & Metabolism|August 27, 2020
Machine-learning-based early prediction of end-stage renal disease in patients with diabetic kidney disease using clinical trials dataSunil Belur Nagaraj, Michelle J Pena, Wenjun Ju, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
A novel dictionary for neonatal EEG seizure detection using atomic decompositionSunil Belur Nagaraj, Nathan Stevenson, William Marnane, et al.
Artificial Intelligence in Medicine|April 20, 2021
STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoringShreyasi Pathak, Changqing Lu, Sunil Belur Nagaraj, et al.
IEEE Transactions on Bio-Medical Engineering|October 21, 2014
Neonatal seizure detection using atomic decomposition with a novel dictionarySunil Belur Nagaraj, Nathan J Stevenson, William P Marnane, et al.
The American Journal of Emergency Medicine|September 30, 2025
Early sepsis prediction in the emergency department using machine learningRaymond J van Wijk, Sunil Belur Nagaraj, Jan C Ter Maaten, et al.
Anesthesia and Analgesia|April 15, 2020
Predicting Deep Hypnotic State From Sleep Brain Rhythms Using Deep Learning: A Data-Repurposing ApproachSunil Belur Nagaraj, Sowmya M Ramaswamy, Maud A S Weerink, et al.
Cancers|June 2, 2021
A Classification Approach for Cancer Survivors from Those Cancer-Free, Based on Health Behaviors: Analysis of the Lifelines CohortFrancisco O Cortés-Ibañez, Sunil Belur Nagaraj, Ludo Cornelissen, et al.
BMJ Health & Care Informatics|September 15, 2025
Automated sepsis prediction from unstructured electronic health records using natural language processing: a retrospective cohort studyLipi Mishra, Sowmya Muchukunte Ramaswamy, Broderick Ivan McCallum-Hee, et al.
Pageof 2