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Sonal Gandhi

Showing results (71-80 of 89) with videos related to

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Current Oncology (Toronto, Ont.)|December 13, 2021
Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic GradeAndrew Lagree, Audrey Shiner, Marie Angeli Alera, et al.
Frontiers in Oncology|May 6, 2024
Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility studyArchya Dasgupta, Daniel DiCenzo, Lakshmanan Sannachi, et al.
Scientific Reports|August 21, 2023
Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancerArchya Dasgupta, Murtuza Saifuddin, Evan McNabb, et al.
British Journal of Cancer|April 19, 2017
Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysisWilliam T Tran, Mehrdad J Gangeh, Lakshmanan Sannachi, et al.
Pilot and Feasibility Studies|March 21, 2019
Ambulatory Toxicity Management (AToM) Pilot: results of a pilot study of a pro-active, telephone-based intervention to improve toxicity management during chemotherapy for breast cancerMonika K Krzyzanowska, Cassandra MacKay, Heekyung Han, et al.
Oncotarget|November 4, 2020
Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancerArchya Dasgupta, Stephen Brade, Lakshmanan Sannachi, et al.
Oncotarget|December 17, 2021
Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasoundArchya Dasgupta, Divya Bhardwaj, Daniel DiCenzo, et al.
Journal of Imaging|April 25, 2025
Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast CancerAdrian Wai Chan, Lakshmanan Sannachi, Daniel Moore-Palhares, et al.
Cancers|August 14, 2025
Validation of a Quantitative Ultrasound Texture Analysis Model for Early Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: A Prospective Serial Imaging StudyDaniel Moore-Palhares, Lakshmanan Sannachi, Adrian Wai Chan, et al.
Genes|September 28, 2023
Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine LearningAudrey Shiner, Alex Kiss, Khadijeh Saednia, et al.
Pageof 9

Showing results (71-80 of 89) with videos related to

Sort By:
Pageof 9
Current Oncology (Toronto, Ont.)|December 13, 2021
Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic GradeAndrew Lagree, Audrey Shiner, Marie Angeli Alera, et al.
Frontiers in Oncology|May 6, 2024
Quantitative ultrasound radiomics guided adaptive neoadjuvant chemotherapy in breast cancer: early results from a randomized feasibility studyArchya Dasgupta, Daniel DiCenzo, Lakshmanan Sannachi, et al.
Scientific Reports|August 21, 2023
Novel MRI-guided focussed ultrasound stimulated microbubble radiation enhancement treatment for breast cancerArchya Dasgupta, Murtuza Saifuddin, Evan McNabb, et al.
British Journal of Cancer|April 19, 2017
Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysisWilliam T Tran, Mehrdad J Gangeh, Lakshmanan Sannachi, et al.
Pilot and Feasibility Studies|March 21, 2019
Ambulatory Toxicity Management (AToM) Pilot: results of a pilot study of a pro-active, telephone-based intervention to improve toxicity management during chemotherapy for breast cancerMonika K Krzyzanowska, Cassandra MacKay, Heekyung Han, et al.
Oncotarget|November 4, 2020
Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancerArchya Dasgupta, Stephen Brade, Lakshmanan Sannachi, et al.
Oncotarget|December 17, 2021
Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasoundArchya Dasgupta, Divya Bhardwaj, Daniel DiCenzo, et al.
Journal of Imaging|April 25, 2025
Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast CancerAdrian Wai Chan, Lakshmanan Sannachi, Daniel Moore-Palhares, et al.
Cancers|August 14, 2025
Validation of a Quantitative Ultrasound Texture Analysis Model for Early Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: A Prospective Serial Imaging StudyDaniel Moore-Palhares, Lakshmanan Sannachi, Adrian Wai Chan, et al.
Genes|September 28, 2023
Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine LearningAudrey Shiner, Alex Kiss, Khadijeh Saednia, et al.
Pageof 9