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34 results on '"Laur, Olga"'

2. Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning

Author

Gupta1, Vikash, Roth, Holger, Buch3, Varun, Rockenbach, Marcio A. B. C., White, Richard D, Yang, Dong, Laur, Olga, Ghoshhajra, Brian, Dayan, Ittai, Xu, Daguang, Flores, Mona G., and Erdal, Barbaros Selnur

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, I.2.10
Abstract

The training of deep learning models typically requires extensive data, which are not readily available as large well-curated medical-image datasets for development of artificial intelligence (AI) models applied in Radiology. Recognizing the potential for transfer learning (TL) to allow a fully trained model from one institution to be fine-tuned by another institution using a much small local dataset, this report describes the challenges, methodology, and benefits of TL within the context of developing an AI model for a basic use-case, segmentation of Left Ventricular Myocardium (LVM) on images from 4-dimensional coronary computed tomography angiography. Ultimately, our results from comparisons of LVM segmentation predicted by a model locally trained using random initialization, versus one training-enhanced by TL, showed that a use-case model initiated by TL can be developed with sparse labels with acceptable performance. This process reduces the time required to build a new model in the clinical environment at a different institution., Comment: 8 pages, 5 figures, pre-print

Published
2020

15. APC-20-0005_Supplemental_Appendix_1_-_Pre-Intervention_Survey_Instrument - Cross-Residency Radiologic/Pathologic Correlation Curriculum: Teaching Correlation of Surgical Specimens With Imaging

Author

DeSimone, Mia S., Ariadne K. DeSimone, Sun, Ellen X., Laur, Olga, Nityanand P. Miskin, Brock, Jane E., and Matalon, Shanna A.

Subjects
Medicine
Abstract

APC-20-0005_Supplemental_Appendix_1_-_Pre-Intervention_Survey_Instrument for Cross-Residency Radiologic/Pathologic Correlation Curriculum: Teaching Correlation of Surgical Specimens With Imaging by Mia S. DeSimone, Ariadne K. DeSimone, Ellen X. Sun, Olga Laur, Nityanand P. Miskin, Jane E. Brock and Shanna A. Matalon in Academic Pathology

Published
2020
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16. APC-20-0005_Supplemental_Appendix_1_Legend - Cross-Residency Radiologic/Pathologic Correlation Curriculum: Teaching Correlation of Surgical Specimens With Imaging

Author

DeSimone, Mia S., Ariadne K. DeSimone, Sun, Ellen X., Laur, Olga, Nityanand P. Miskin, Brock, Jane E., and Matalon, Shanna A.

Subjects
education, Medicine
Abstract

APC-20-0005_Supplemental_Appendix_1_Legend for Cross-Residency Radiologic/Pathologic Correlation Curriculum: Teaching Correlation of Surgical Specimens With Imaging by Mia S. DeSimone, Ariadne K. DeSimone, Ellen X. Sun, Olga Laur, Nityanand P. Miskin, Jane E. Brock and Shanna A. Matalon in Academic Pathology

Published
2020
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22. Hypochloremia and Diuretic Resistance in Heart Failure

Author

Hanberg, Jennifer S., primary, Rao, Veena, additional, ter Maaten, Jozine M., additional, Laur, Olga, additional, Brisco, Meredith A., additional, Perry Wilson, F., additional, Grodin, Justin L., additional, Assefa, Mahlet, additional, Samuel Broughton, J., additional, Planavsky, Noah J., additional, Ahmad, Tariq, additional, Bellumkonda, Lavanya, additional, Wilson Tang, W. H., additional, Parikh, Chirag R., additional, and Testani, Jeffrey M., additional

Published
2016
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25. Rapid and Highly Accurate Prediction of Poor Loop Diuretic Natriuretic Response in Patients With Heart Failure

Author

Testani, Jeffrey M., primary, Hanberg, Jennifer S., additional, Cheng, Susan, additional, Rao, Veena, additional, Onyebeke, Chukwuma, additional, Laur, Olga, additional, Kula, Alexander, additional, Chen, Michael, additional, Wilson, F. Perry, additional, Darlington, Andrew, additional, Bellumkonda, Lavanya, additional, Jacoby, Daniel, additional, Tang, W.H. Wilson, additional, and Parikh, Chirag R., additional

Published
2016
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34. Imaging of iatrogenic oesophageal injuries using optimized CT oesophageal leak protocol: pearls and pitfalls.

Author

Madan, Rachna, Laur, Olga, Crudup, Breland, Peavy, Latia, and Carter, Brett W

Subjects
*ESOPHAGEAL perforation, *IATROGENIC diseases, *COMPUTED tomography, *POSTOPERATIVE care, *CROSS-sectional method
Abstract

Iatrogenic injury to the oesophagus is a serious complication which is increasingly seen in clinical practice secondary to expansion and greater acceptability of surgical and endoscopic oesophageal procedures. Morbidity and mortality following such injury is high. This is mostly due to an inflammatory response to gastric contents in the mediastinum, and the negative intrathoracic pressures that may further draw out oesophageal contents into the mediastinum leading to mediastinitis. Subsequently, pulmonary complications such as pneumonia or abscess may ensue leading to rapid clinical deterioration. Optimized and timely cross-sectional imaging evaluation is necessary for early and aggressive management of these complications. The goal of this review is to make the radiologist aware of the importance of early and accurate identification of postoperative oesophageal injury using optimized CT imaging protocols and use of oral contrast. Specifically, it is critical to differentiate benign post-operative findings, such as herniated viscus or redundant anastomosis, from clinically significant postoperative complications as this helps guide appropriate management. Advantages and drawbacks of other diagnostic methods, such as contrast oesophagogram, are also discussed. [ABSTRACT FROM AUTHOR]

Published
2018
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