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Tanmay Nath

Showing results (1-10 of 17) with videos related to

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Journal of Clinical Hypertension (Greenwich, Conn.)|November 30, 2021
Machine learning approach to predicting albuminuria in persons with type 2 diabetes: An analysis of the LOOK AHEAD CohortZeid Khitan, Tanmay Nath, Prasanna Santhanam
Journal of Clinical Hypertension (Greenwich, Conn.)|June 5, 2020
DXA measured body composition predicts blood pressure using machine learning methodsTanmay Nath, Rexford S Ahima, Prasanna Santhanam
Plos One|March 31, 2021
Body fat predicts exercise capacity in persons with Type 2 Diabetes Mellitus: A machine learning approachTanmay Nath, Rexford S Ahima, Prasanna Santhanam
Neuroimage|December 31, 2022
A machine learning based approach towards high-dimensional mediation analysisTanmay Nath, Brian Caffo, Tor Wager, et al.
Plos One|May 21, 2020
Artificial intelligence may offer insight into factors determining individual TSH levelPrasanna Santhanam, Tanmay Nath, Faiz Khan Mohammad, et al.
The Journal of Clinical Endocrinology and Metabolism|April 7, 2022
Relationship Between TSH Levels and Cognition in the Young Adult: An Analysis of the Human Connectome Project DataPrasanna Santhanam, Tanmay Nath, Martin A Lindquist, et al.
Scientific Reports|August 1, 2024
Early predictive values of clinical assessments for ARDS mortality: a machine-learning approachNing Ding, Tanmay Nath, Mahendra Damarla, et al.
Nature Protocols|June 23, 2019
Using DeepLabCut for 3D markerless pose estimation across species and behaviorsTanmay Nath, Alexander Mathis, An Chi Chen, et al.
Molecular Autism|March 16, 2018
Network-specific sex differentiation of intrinsic brain function in males with autismDorothea L Floris, Meng-Chuan Lai, Tanmay Nath, et al.
Diabetes & Metabolic Syndrome|March 3, 2023
Artificial intelligence and body compositionPrasanna Santhanam, Tanmay Nath, Cheng Peng, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Journal of Clinical Hypertension (Greenwich, Conn.)|November 30, 2021
Machine learning approach to predicting albuminuria in persons with type 2 diabetes: An analysis of the LOOK AHEAD CohortZeid Khitan, Tanmay Nath, Prasanna Santhanam
Journal of Clinical Hypertension (Greenwich, Conn.)|June 5, 2020
DXA measured body composition predicts blood pressure using machine learning methodsTanmay Nath, Rexford S Ahima, Prasanna Santhanam
Plos One|March 31, 2021
Body fat predicts exercise capacity in persons with Type 2 Diabetes Mellitus: A machine learning approachTanmay Nath, Rexford S Ahima, Prasanna Santhanam
Neuroimage|December 31, 2022
A machine learning based approach towards high-dimensional mediation analysisTanmay Nath, Brian Caffo, Tor Wager, et al.
Plos One|May 21, 2020
Artificial intelligence may offer insight into factors determining individual TSH levelPrasanna Santhanam, Tanmay Nath, Faiz Khan Mohammad, et al.
The Journal of Clinical Endocrinology and Metabolism|April 7, 2022
Relationship Between TSH Levels and Cognition in the Young Adult: An Analysis of the Human Connectome Project DataPrasanna Santhanam, Tanmay Nath, Martin A Lindquist, et al.
Scientific Reports|August 1, 2024
Early predictive values of clinical assessments for ARDS mortality: a machine-learning approachNing Ding, Tanmay Nath, Mahendra Damarla, et al.
Nature Protocols|June 23, 2019
Using DeepLabCut for 3D markerless pose estimation across species and behaviorsTanmay Nath, Alexander Mathis, An Chi Chen, et al.
Molecular Autism|March 16, 2018
Network-specific sex differentiation of intrinsic brain function in males with autismDorothea L Floris, Meng-Chuan Lai, Tanmay Nath, et al.
Diabetes & Metabolic Syndrome|March 3, 2023
Artificial intelligence and body compositionPrasanna Santhanam, Tanmay Nath, Cheng Peng, et al.
Pageof 2