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Mohammad Peikari

Showing results (1-10 of 9) with videos related to

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Cytometry. Part a : the Journal of the International Society for Analytical Cytology|October 5, 2017
Automatic cellularity assessment from post-treated breast surgical specimensMohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, et al.
Scientific Reports|May 10, 2018
A Cluster-then-label Semi-supervised Learning Approach for Pathology Image ClassificationMohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, et al.
IEEE Transactions on Medical Imaging|August 25, 2015
Triaging Diagnostically Relevant Regions from Pathology Whole Slides of Breast Cancer: A Texture Based ApproachMohammad Peikari, Mehrdad J Gangeh, Judit Zubovits, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 19, 2011
Effects of ultrasound section-thickness on brachytherapy needle tip localization errorMohammad Peikari, Thomas Kuiran Chen, Andras Lasso, et al.
Medical Physics|January 10, 2012
Characterization of ultrasound elevation beamwidth artifacts for prostate brachytherapy needle insertionMohammad Peikari, Thomas Kuriran Chen, Anras Lasso, et al.
Scientific Reports|October 3, 2019
Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden AssessmentShazia Akbar, Mohammad Peikari, Sherine Salama, et al.
Plos One|September 10, 2025
Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank CohortKarim Taha, Heather J Ross, Mohammad Peikari, et al.
European Heart Journal. Digital Health|May 22, 2024
Predicting heart failure outcomes by integrating breath-by-breath measurements from cardiopulmonary exercise testing and clinical data through a deep learning survival neural networkHeather J Ross, Mohammad Peikari, Julie K K Vishram-Nielsen, et al.
JACC. Cardiovascular Imaging|May 29, 2026
Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac DysfunctionChristopher Yu, Mohammad Peikari, Dina Labib, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Cytometry. Part a : the Journal of the International Society for Analytical Cytology|October 5, 2017
Automatic cellularity assessment from post-treated breast surgical specimensMohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, et al.
Scientific Reports|May 10, 2018
A Cluster-then-label Semi-supervised Learning Approach for Pathology Image ClassificationMohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, et al.
IEEE Transactions on Medical Imaging|August 25, 2015
Triaging Diagnostically Relevant Regions from Pathology Whole Slides of Breast Cancer: A Texture Based ApproachMohammad Peikari, Mehrdad J Gangeh, Judit Zubovits, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 19, 2011
Effects of ultrasound section-thickness on brachytherapy needle tip localization errorMohammad Peikari, Thomas Kuiran Chen, Andras Lasso, et al.
Medical Physics|January 10, 2012
Characterization of ultrasound elevation beamwidth artifacts for prostate brachytherapy needle insertionMohammad Peikari, Thomas Kuriran Chen, Anras Lasso, et al.
Scientific Reports|October 3, 2019
Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden AssessmentShazia Akbar, Mohammad Peikari, Sherine Salama, et al.
Plos One|September 10, 2025
Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank CohortKarim Taha, Heather J Ross, Mohammad Peikari, et al.
European Heart Journal. Digital Health|May 22, 2024
Predicting heart failure outcomes by integrating breath-by-breath measurements from cardiopulmonary exercise testing and clinical data through a deep learning survival neural networkHeather J Ross, Mohammad Peikari, Julie K K Vishram-Nielsen, et al.
JACC. Cardiovascular Imaging|May 29, 2026
Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac DysfunctionChristopher Yu, Mohammad Peikari, Dina Labib, et al.
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