Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource, 1 online resource.
- Language
-
Englisch
- Bibliographic citation
-
Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy ; volume:3 ; number:1 ; day:30 ; month:3 ; year:2023 ; pages:1-12 ; date:12.2023
Communications medicine ; 3, Heft 1 (30.3.2023), 1-12, 12.2023
- Creator
-
Chitalia, Rhea
Miliotis, Marios
Jahani, Nariman
Tastsoglou, Spyros
McDonald, Elizabeth S.
Belenky, Vivian
Cohen, Eric A.
Newitt, David
van’t Veer, Laura J.
Esserman, Laura
Hylton, Nola
DeMichele, Angela
Hatzigeorgiou, Artemis
Kontos, Despina
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1038/s43856-023-00273-1
- URN
-
urn:nbn:de:101:1-2023081521193118137876
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:45 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Chitalia, Rhea
- Miliotis, Marios
- Jahani, Nariman
- Tastsoglou, Spyros
- McDonald, Elizabeth S.
- Belenky, Vivian
- Cohen, Eric A.
- Newitt, David
- van’t Veer, Laura J.
- Esserman, Laura
- Hylton, Nola
- DeMichele, Angela
- Hatzigeorgiou, Artemis
- Kontos, Despina
- SpringerLink (Online service)
Other Objects (12)
A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis
Postoperative recurrence in locally advanced rectal cancer: how does neoadjuvant treatment affect recurrence pattern?
Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer
Evolutionary Learning-Derived Clinical-Radiomic Models for Predicting Early Recurrence of Hepatocellular Carcinoma after Resection
Delta Radiomic Features Predict Resection Margin Status and Overall Survival in Neoadjuvant-Treated Pancreatic Cancer Patients
Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer
Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT
CT-based radiomic signatures for prediction of pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy
A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis
Postoperative recurrence in locally advanced rectal cancer: how does neoadjuvant treatment affect recurrence pattern?
Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer
Evolutionary Learning-Derived Clinical-Radiomic Models for Predicting Early Recurrence of Hepatocellular Carcinoma after Resection
Delta Radiomic Features Predict Resection Margin Status and Overall Survival in Neoadjuvant-Treated Pancreatic Cancer Patients
Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer
Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT
CT-based radiomic signatures for prediction of pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy
A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis
Postoperative recurrence in locally advanced rectal cancer: how does neoadjuvant treatment affect recurrence pattern?
Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer
Evolutionary Learning-Derived Clinical-Radiomic Models for Predicting Early Recurrence of Hepatocellular Carcinoma after Resection
Delta Radiomic Features Predict Resection Margin Status and Overall Survival in Neoadjuvant-Treated Pancreatic Cancer Patients
Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy
Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer
Machine learning-based radiomic analysis and growth visualization for ablation site recurrence diagnosis in follow-up CT