Ha RS - Search Results

1

Diffuse optical tomography of the breast: a potential modifiable biomarker of breast cancer risk with neoadjuvant chemotherapy.

Altoe ML, Marone A, Kim HK, Kalinsky K, Hershman DL, Hielscher AH, Ha RS. Altoe ML, et al. Among authors: ha rs. Biomed Opt Express. 2019 Aug 1;10(8):4305-4315. doi: 10.1364/BOE.10.004305. eCollection 2019 Aug 1. Biomed Opt Express. 2019. PMID: 31453012 Free PMC article.

2

Expanding the Criteria for Nipple-Sparing Mastectomy in Patients With Poor Prognostic Features.

Jadeja P, Ha R, Rohde C, Ascherman J, Grant R, Chin C, Connolly E, Kalinsky K, Feldman S, Taback B. Jadeja P, et al. Clin Breast Cancer. 2018 Jun;18(3):229-233. doi: 10.1016/j.clbc.2017.08.010. Epub 2017 Aug 24. Clin Breast Cancer. 2018. PMID: 28967559

3

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Ha R, Chang P, Mutasa S, Karcich J, Goodman S, Blum E, Kalinsky K, Liu MZ, Jambawalikar S. Ha R, et al. J Magn Reson Imaging. 2019 Feb;49(2):518-524. doi: 10.1002/jmri.26244. Epub 2018 Aug 21. J Magn Reson Imaging. 2019. PMID: 30129697 Free PMC article.

4

Utility of preoperative breast MRI in patient selection for accelerated partial breast irradiation by different consensus guidelines.

Chin C, Consul N, Jadeja P, Kwak E, Patel S, Wynn R, Hershman D, Connolly EP, Ha R. Chin C, et al. Breast J. 2019 Jan;25(1):160-162. doi: 10.1111/tbj.13185. Epub 2018 Dec 21. Breast J. 2019. PMID: 30576036 No abstract available.

5

Use of a convolutional neural network-based mammographic evaluation to predict breast cancer recurrence among women with hormone receptor-positive operable breast cancer.

McGuinness JE, Ro V, Mutasa S, Pan S, Hu J, Trivedi MS, Accordino MK, Kalinsky K, Hershman DL, Ha RS, Crew KD. McGuinness JE, et al. Among authors: ha rs. Breast Cancer Res Treat. 2022 Jul;194(1):35-47. doi: 10.1007/s10549-022-06614-3. Epub 2022 May 16. Breast Cancer Res Treat. 2022. PMID: 35575954

6

Effect of Longitudinal Variation in Tumor Volume Estimation for MRI-guided Personalization of Breast Cancer Neoadjuvant Treatment.

Onishi N, Bareng TJ, Gibbs J, Li W, Price ER, Joe BN, Kornak J, Esserman LJ, Newitt DC, Hylton NM; I-SPY 2 Imaging Working Group; I-SPY 2 Investigator Network. Onishi N, et al. Radiol Imaging Cancer. 2023 Jul;5(4):e220126. doi: 10.1148/rycan.220126. Radiol Imaging Cancer. 2023. PMID: 37505107 Free PMC article.

7

Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic Dataset.

Ha R, Chang P, Karcich J, Mutasa S, Pascual Van Sant E, Liu MZ, Jambawalikar S. Ha R, et al. Acad Radiol. 2019 Apr;26(4):544-549. doi: 10.1016/j.acra.2018.06.020. Epub 2018 Jul 31. Acad Radiol. 2019. PMID: 30072292 Free PMC article.

8

Optical coherence tomography holds promise to transform the diagnostic anatomic pathology gross evaluation process.

Mojahed D, Applegate M, Guo H, Taback B, Ha R, Hibshoosh H, Hendon C. Mojahed D, et al. J Biomed Opt. 2022 Sep;27(9):096003. doi: 10.1117/1.JBO.27.9.096003. J Biomed Opt. 2022. PMID: 36050827 Free PMC article.

9

Breast cancer risk prediction combining a convolutional neural network-based mammographic evaluation with clinical factors.

Michel A, Ro V, McGuinness JE, Mutasa S, Terry MB, Tehranifar P, May B, Ha R, Crew KD. Michel A, et al. Breast Cancer Res Treat. 2023 Jul;200(2):237-245. doi: 10.1007/s10549-023-06966-4. Epub 2023 May 20. Breast Cancer Res Treat. 2023. PMID: 37209183

10

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study.

Ha R, Mema E, Guo X, Mango V, Desperito E, Ha J, Wynn R, Zhao B. Ha R, et al. Quant Imaging Med Surg. 2016 Apr;6(2):144-50. doi: 10.21037/qims.2016.03.03. Quant Imaging Med Surg. 2016. PMID: 27190766 Free PMC article.

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