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Hong-Ren Su

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

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Biomedical Optics Express|June 6, 2020
Lymphatic vessel segmentation in optical coherence tomography by adding U-Net-based CNN for artifact minimizationPei-Yu Lai, Chung-Hsing Chang, Hong-Ren Su, et al.
Journal of Cognitive Neuroscience|November 25, 2003
Functional MR images and scientific inference: reproducibility mapsMichelle Liou, Hong-Ren Su, Juin-Der Lee, et al.
Neuroimage|October 18, 2005
A method for generating reproducible evidence in fMRI studiesMichelle Liou, Hong-Ren Su, Juin-Der Lee, et al.
JMIR Medical Informatics|June 11, 2026
AI-Powered Resting 12-Lead Electrocardiogram Algorithm for Predicting Low Peak Oxygen Consumption: Development and Validation StudyShu-Chun Huang, Tieh-Cheng Fu, Michelle Liou, et al.
Scientific Reports|February 20, 2019
Noninvasive prediction of Blood Lactate through a machine learning-based approachShu-Chun Huang, Richard Casaburi, Ming-Feng Liao, et al.
IEEE Transactions on Medical Imaging|January 24, 2009
MR image segmentation using a power transformation approachJuin-Der Lee, Hong-Ren Su, Philip E Cheng, et al.
Journal of Biomedical Optics|February 5, 2013
Semiautomatic and rapid quantification of heartbeat parameters in Drosophila using optical coherence tomography imagingShou-Yuan Guo, Fang-Tsu Liao, Ming-Tsan Su, et al.
Psychophysiology|February 12, 2009
Beyond p-values: averaged and reproducible evidence in fMRI experimentsMichelle Liou, Hong-Ren Su, Alexander N Savostyanov, et al.
Anesthesia and Analgesia|August 5, 2025
Camera-Based Photoplethysmography for Measuring Heartbeat Intervals During General AnesthesiaHui-Hsuan Ke, Chien-Kun Ting, Yi-Ming Huang, et al.
Frontiers in Physiology|November 13, 2023
Prediction for blood lactate during exercise using an artificial intelligence-Enabled electrocardiogram: a feasibility studyShu-Chun Huang, Chen-Hung Lee, Chih-Chin Hsu, et al.
Pageof 1

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

Sort By:
Pageof 1
Biomedical Optics Express|June 6, 2020
Lymphatic vessel segmentation in optical coherence tomography by adding U-Net-based CNN for artifact minimizationPei-Yu Lai, Chung-Hsing Chang, Hong-Ren Su, et al.
Journal of Cognitive Neuroscience|November 25, 2003
Functional MR images and scientific inference: reproducibility mapsMichelle Liou, Hong-Ren Su, Juin-Der Lee, et al.
Neuroimage|October 18, 2005
A method for generating reproducible evidence in fMRI studiesMichelle Liou, Hong-Ren Su, Juin-Der Lee, et al.
JMIR Medical Informatics|June 11, 2026
AI-Powered Resting 12-Lead Electrocardiogram Algorithm for Predicting Low Peak Oxygen Consumption: Development and Validation StudyShu-Chun Huang, Tieh-Cheng Fu, Michelle Liou, et al.
Scientific Reports|February 20, 2019
Noninvasive prediction of Blood Lactate through a machine learning-based approachShu-Chun Huang, Richard Casaburi, Ming-Feng Liao, et al.
IEEE Transactions on Medical Imaging|January 24, 2009
MR image segmentation using a power transformation approachJuin-Der Lee, Hong-Ren Su, Philip E Cheng, et al.
Journal of Biomedical Optics|February 5, 2013
Semiautomatic and rapid quantification of heartbeat parameters in Drosophila using optical coherence tomography imagingShou-Yuan Guo, Fang-Tsu Liao, Ming-Tsan Su, et al.
Psychophysiology|February 12, 2009
Beyond p-values: averaged and reproducible evidence in fMRI experimentsMichelle Liou, Hong-Ren Su, Alexander N Savostyanov, et al.
Anesthesia and Analgesia|August 5, 2025
Camera-Based Photoplethysmography for Measuring Heartbeat Intervals During General AnesthesiaHui-Hsuan Ke, Chien-Kun Ting, Yi-Ming Huang, et al.
Frontiers in Physiology|November 13, 2023
Prediction for blood lactate during exercise using an artificial intelligence-Enabled electrocardiogram: a feasibility studyShu-Chun Huang, Chen-Hung Lee, Chih-Chin Hsu, et al.
Pageof 1