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Chris McIntosh

Showing results (21-30 of 54) with videos related to

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Optics Express|July 28, 2016
Narrow-band 1 W source at 257 nm using frequency quadrupled passively Q-switched Yb:YAG laserLew Goldberg, Brian Cole, Chris McIntosh, et al.
Optics Express|February 4, 2009
Reduction of timing jitter in a Q-Switched Nd:YAG laser by direct bleaching of a Cr4+:YAG saturable absorberBrian Cole, Lew Goldberg, C Ward Trussell, et al.
The Canadian Journal of Cardiology|July 18, 2024
Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial IntelligenceTina Binesh Marvasti, Yuan Gao, Kevin R Murray, et al.
BMC Medical Imaging|July 15, 2025
Non-invasive liver fibrosis screening on CT images using radiomicsJay J Yoo, Khashayar Namdar, Sean Carey, et al.
JACC. Cardiooncology|April 22, 2026
Risk Prediction in Cardio-Oncology: Conceptual and Methodological Considerations: JACC: CardioOncology State-of-the-Art ReviewJonathan Sen, Eitan Amir, Peter C Austin, et al.
Heart Rhythm|November 8, 2024
Machine Learning Identifies Arrhythmogenic Features of QRS Fragmentation in Human Cardiomyopathy: Implications for Improving Risk StratificationCathy Ong Ly, Adrian M Suszko, Nathan C Denham, et al.
European Radiology|August 23, 2025
Utility of machine learning for predicting severe chronic thromboembolic pulmonary hypertension based on CT metrics in a surgical cohortMicah Grubert Van Iderstine, Sangwook Kim, Gauri Rani Karur, et al.
European Radiology|November 28, 2025
Reply to the Letter to the Editor: Rethinking the clinical utility of machine learning for CTEPH severityMicah Grubert Van Iderstine, Sangwook Kim, Gauri Rani Karur, et al.
Physics in Medicine and Biology|December 19, 2019
External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classificationMattea L Welch, Chris McIntosh, Alberto Traverso, et al.
Hematology (Amsterdam, Netherlands)|April 2, 2026
Machine learning in the prediction of liver iron concentration and iron chelation therapy adjustmentJoanna Bao-Ern Loh, Sangwook Kim, Richard Ward, et al.
Pageof 6

Showing results (21-30 of 54) with videos related to

Sort By:
Pageof 6
Optics Express|July 28, 2016
Narrow-band 1 W source at 257 nm using frequency quadrupled passively Q-switched Yb:YAG laserLew Goldberg, Brian Cole, Chris McIntosh, et al.
Optics Express|February 4, 2009
Reduction of timing jitter in a Q-Switched Nd:YAG laser by direct bleaching of a Cr4+:YAG saturable absorberBrian Cole, Lew Goldberg, C Ward Trussell, et al.
The Canadian Journal of Cardiology|July 18, 2024
Unlocking Tomorrow's Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial IntelligenceTina Binesh Marvasti, Yuan Gao, Kevin R Murray, et al.
BMC Medical Imaging|July 15, 2025
Non-invasive liver fibrosis screening on CT images using radiomicsJay J Yoo, Khashayar Namdar, Sean Carey, et al.
JACC. Cardiooncology|April 22, 2026
Risk Prediction in Cardio-Oncology: Conceptual and Methodological Considerations: JACC: CardioOncology State-of-the-Art ReviewJonathan Sen, Eitan Amir, Peter C Austin, et al.
Heart Rhythm|November 8, 2024
Machine Learning Identifies Arrhythmogenic Features of QRS Fragmentation in Human Cardiomyopathy: Implications for Improving Risk StratificationCathy Ong Ly, Adrian M Suszko, Nathan C Denham, et al.
European Radiology|August 23, 2025
Utility of machine learning for predicting severe chronic thromboembolic pulmonary hypertension based on CT metrics in a surgical cohortMicah Grubert Van Iderstine, Sangwook Kim, Gauri Rani Karur, et al.
European Radiology|November 28, 2025
Reply to the Letter to the Editor: Rethinking the clinical utility of machine learning for CTEPH severityMicah Grubert Van Iderstine, Sangwook Kim, Gauri Rani Karur, et al.
Physics in Medicine and Biology|December 19, 2019
External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classificationMattea L Welch, Chris McIntosh, Alberto Traverso, et al.
Hematology (Amsterdam, Netherlands)|April 2, 2026
Machine learning in the prediction of liver iron concentration and iron chelation therapy adjustmentJoanna Bao-Ern Loh, Sangwook Kim, Richard Ward, et al.
Pageof 6