Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Manjiri M. Bakre"'
Autor:
Mallikarjuna Siraganahalli Eshwaraiah, Aparna Gunda, Govind Babu Kanakasetty, Manjiri M. Bakre
Publikováno v:
Cancer Medicine, Vol 12, Iss 12, Pp 13342-13351 (2023)
Abstract Background Assessment of Ki67 by immunohistochemistry (IHC) has limited utility in clinical practice owing to analytical validity issues. According to International Ki67 Working Group (IKWG) guidelines, treatment should be guided by a progno
Externí odkaz:
https://doaj.org/article/1f006e3f91d44800ba0e831c04a2685c
Autor:
Dinesh Chandra Doval, Anurag Mehta, S.P. Somashekhar, Aparna Gunda, Gurpreet Singh, Amanjit Bal, Siddhant Khare, Chandra Prakash V Serkad, Manjula Adinarayan, Naveen Krishnamoorthy, Devanhalli Govinda Vijay, Radha Anantakrishnan, G.S. Bhattacharyya, Manjiri M. Bakre
Publikováno v:
Breast, Vol 59, Iss , Pp 1-7 (2021)
Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach
Externí odkaz:
https://doaj.org/article/37d33ca9bd764c319e1199039a81fc60
Autor:
Aditya K. Sengupta, Aparna Gunda, Sukriti Malpani, Chandra Prakash V. Serkad, Chetana Basavaraj, Ashok Bapat, Manjiri M. Bakre
Publikováno v:
Cancer Medicine, Vol 9, Iss 21, Pp 7810-7818 (2020)
Abstract Background CanAssist Breast (CAB) is a prognostic test for early stage hormone receptor‐positive (HR+), human epidermal growth factor receptor 2 negative (HER2−) breast cancer patients, validated on Indian and Caucasian patients. The 21
Externí odkaz:
https://doaj.org/article/ecf2a697530b470ca1b26e99421d37d3
Autor:
Manjiri M. Bakre, Charusheila Ramkumar, Arun Kumar Attuluri, Chetana Basavaraj, Chandra Prakash, Ljubomir Buturovic, Lekshmi Madhav, Nirupama Naidu, Prathima R, S. P. Somashekhar, Sudeep Gupta, Dinesh Chandra Doval, Mark D. Pegram
Publikováno v:
Cancer Medicine, Vol 8, Iss 4, Pp 1755-1764 (2019)
Abstract CanAssist‐Breast (CAB) is an immunohistochemistry (IHC)‐based prognostic test for early‐stage Hormone Receptor (HR+)‐positive breast cancer patients. CAB uses a Support Vector Machine (SVM) trained algorithm which utilizes expression
Externí odkaz:
https://doaj.org/article/9e0599c8445a41efaf55c1598f1c78cc
Autor:
Arun Kumar Attuluri, Chandra Prakash V. Serkad, Aparna Gunda, Charusheila Ramkumar, Chetana Basavaraj, Ljubomir Buturovic, Lekshmi Madhav, Nirupama Naidu, Naveen Krishnamurthy, R. Prathima, Suchita Kanaldekar, Manjiri M. Bakre
Publikováno v:
BMC Cancer, Vol 19, Iss 1, Pp 1-10 (2019)
Abstract Background CanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings fo
Externí odkaz:
https://doaj.org/article/2f220efa6fd54db491fdcb096acc2418
Publikováno v:
Breast Cancer Research and Treatment. 196:299-310
Aims Clinicians use multi-gene/biomarker prognostic tests and free online tools to optimize treatment in early ER+/HER2− breast cancer. Here we report the comparison of recurrence risk predictions by CanAssist Breast (CAB), Nottingham Prognostic In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3329dff32f74060d49b9003f8a472b64
https://doi.org/10.1007/s10549-022-06729-7
https://doi.org/10.1007/s10549-022-06729-7
Autor:
H Fiegl, Manjiri M Bakre, S.P. Somashekhar, Christine Brunner, Aparna Gunda, Cristina Saura, Aditya K. Sengupta, Chandra Prakash V Serkad, Susanne Sprung, Patricia Gomez, Daniel Egle, José Antonio Jiménez, Vicente Peg
Publikováno v:
Cancer Research. 81:PS4-47
Background: CanAssist Breast (CAB) is a prognostic test for early stage hormone receptor positive breast cancer patients, that predicts risk of distant recurrence in five years post-diagnosis. Its support vector machine-based algorithm utilizes immun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf029c53d97a30886a39c075e8e3306d
https://doi.org/10.1158/1538-7445.sabcs20-ps4-47
https://doi.org/10.1158/1538-7445.sabcs20-ps4-47
Autor:
Manjiri M Bakre, Aditya K. Sengupta, Chandra Prakash V Serkad, Sukriti Malpani, Aparna Gunda, Ashok Bapat, Chetana Basavaraj
Publikováno v:
Cancer Medicine
Cancer Medicine, Vol 9, Iss 21, Pp 7810-7818 (2020)
Cancer Medicine, Vol 9, Iss 21, Pp 7810-7818 (2020)
Background CanAssist Breast (CAB) is a prognostic test for early stage hormone receptor‐positive (HR+), human epidermal growth factor receptor 2 negative (HER2−) breast cancer patients, validated on Indian and Caucasian patients. The 21‐gene si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf9b72e506e7322ddc9c23f9e3633f88
https://doi.org/10.1002/cam4.3495
https://doi.org/10.1002/cam4.3495
Autor:
Manjula Adinarayan, Mallikarjuna Siraganahalli Eswaraiah, Chetana Basavaraj, Manjiri M Bakre, Sindhu Govindan, Satish Sankaran
Publikováno v:
BMC Cancer, Vol 20, Iss 1, Pp 1-11 (2020)
BMC Cancer
BMC Cancer
Background Anti-Androgen Receptor (AR) therapy holds promise for a subset of AR expressing triple-negative breast cancer (TNBC) patients. However, current AR assays are suboptimal in detecting the dynamic range of AR expression, contributing to its c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44fb3e7659cf0c07dbd36dd216605932
http://link.springer.com/article/10.1186/s12885-020-07218-0
http://link.springer.com/article/10.1186/s12885-020-07218-0
Autor:
S.P. Somashekhar, Mallikarjuna Se, Satish Sankaran, Chandra Prakash Sv, Dinesh Shet, Rajeev Kumar, Krishna Prasad, Shekhar Patil, Manjiri M Bakre, Jyoti Bajpai Dikshit
Publikováno v:
Indian Journal of Surgical Oncology. 12:21-29
CanAssist Breast (CAB) has thus far been validated on a retrospective cohort of 1123 patients who are mostly Indians. Distant metastasis–free survival (DMFS) of more than 95% was observed with significant separation (P
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b190a6c02bc572fb140f429a1a8d7db
https://doi.org/10.1007/s13193-019-01014-4
https://doi.org/10.1007/s13193-019-01014-4