Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Sumeet Shinde"'
Publikováno v:
PeerJ Computer Science, Vol 7, p e622 (2021)
Purpose Existing class activation mapping (CAM) techniques extract the feature maps only from a single layer of the convolutional neural net (CNN), generally from the final layer and then interpolate to upsample to the original image resolution to lo
Externí odkaz:
https://doaj.org/article/038b0a0291694ef897af851610c7f346
Autor:
Apoorva Safai, Sumeet Shinde, Manali Jadhav, Tanay Chougule, Abhilasha Indoria, Manoj Kumar, Vani Santosh, Shumyla Jabeen, Manish Beniwal, Subhash Konar, Jitender Saini, Madhura Ingalhalikar
Publikováno v:
Frontiers in Neurology, Vol 12 (2021)
Rationale and Objectives: To build a machine learning-based diagnostic model that can accurately distinguish adult supratentorial extraventricular ependymoma (STEE) from similarly appearing high-grade gliomas (HGG) using quantitative radiomic signatu
Externí odkaz:
https://doaj.org/article/52da8ff5baf649399550d395223dea6a
Autor:
Sumeet Shinde, Shweta Prasad, Yash Saboo, Rishabh Kaushick, Jitender Saini, Pramod Kumar Pal, Madhura Ingalhalikar
Publikováno v:
NeuroImage: Clinical, Vol 22, Iss , Pp - (2019)
Neuromelanin sensitive magnetic resonance imaging (NMS-MRI) has been crucial in identifying abnormalities in the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) as PD is characterized by loss of dopaminergic neurons in the SNc. Curre
Externí odkaz:
https://doaj.org/article/b8a7ae7a3f63474c8d219e0d4c497dd5
Publikováno v:
Journal of Pharmaceutical Research International. :218-226
Background: Hayes Martin maneuver (HMM) and Anterograde dissection technique (ADT) were originally described in 1951 as a means of preserving the marginal mandibular nerve (MMN) during level 1B clearance in a neck dissection procedure address the cer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::933c6e21f11798ab48c8a97140ed6478
https://doi.org/10.9734/jpri/2021/v33i64a35360
https://doi.org/10.9734/jpri/2021/v33i64a35360
Autor:
Sumeet Shinde, Gopikrishna Deshpande, Archith Rajan, Arnav Karmarkar, Madhura Ingalhalikar, D. Rangaprakash
Publikováno v:
IEEE Trans Biomed Eng
Objective: The larger sample sizes available from multi-site publicly available neuroimaging data repositories makes machine-learning based diagnostic classification of mental disorders more feasible by alleviating the curse of dimensionality. Howeve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::161d82764dda9bdc28be45d744e5f712
https://doi.org/10.1109/tbme.2021.3080259
https://doi.org/10.1109/tbme.2021.3080259
Autor:
Jitender Saini, Manoj Kumar, Abhilasha Indoria, Vani Santosh, Subhash Kanti Konar, Shumyla Jabeen, Apoorva Safai, Manali Jadhav, Tanay Chougule, Madhura Ingalhalikar, Sumeet Shinde, Manish Beniwal
Publikováno v:
Frontiers in Neurology, Vol 12 (2021)
Frontiers in Neurology
Frontiers in Neurology
Rationale and Objectives: To build a machine learning-based diagnostic model that can accurately distinguish adult supratentorial extraventricular ependymoma (STEE) from similarly appearing high-grade gliomas (HGG) using quantitative radiomic signatu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::399999e3da14ca21317b74a34b697df4
https://www.frontiersin.org/articles/10.3389/fneur.2021.648092/full
https://www.frontiersin.org/articles/10.3389/fneur.2021.648092/full
Publikováno v:
Acta Scientific Dental Scienecs. 4:114-116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33d746843433e206e4286b475a4aa680
https://doi.org/10.31080/asds.2020.04.0898
https://doi.org/10.31080/asds.2020.04.0898
Publikováno v:
Radiomics and Radiogenomics in Neuro-oncology ISBN: 9783030401238
RNO-AI@MICCAI
RNO-AI@MICCAI
Radiomics based multi-variate models and state-of-art convolutional neural networks (CNNs) have demonstrated their usefulness for predicting IDH genotype in gliomas from multi-modal brain MRI images. However, it is not yet clear on how well these mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c9c0e7630410561720b8b3ba761c7cd
https://doi.org/10.1007/978-3-030-40124-5_6
https://doi.org/10.1007/978-3-030-40124-5_6
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783030598600
MLMI@MICCAI
MLMI@MICCAI
Application of deep neural networks in learning underlying dermoscopic patterns and classifying skin-lesion pathology is crucial. It can help in early diagnosis which can lead to timely therapeutic intervention and efficacy. To establish the clinical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9a7c576758c261eea7363e1bb0e498c
https://doi.org/10.1007/978-3-030-59861-7_62
https://doi.org/10.1007/978-3-030-59861-7_62
Publikováno v:
PeerJ Computer Science
PeerJ Computer Science, Vol 7, p e622 (2021)
PeerJ Computer Science, Vol 7, p e622 (2021)
Purpose Existing class activation mapping (CAM) techniques extract the feature maps only from a single layer of the convolutional neural net (CNN), generally from the final layer and then interpolate to upsample to the original image resolution to lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1821caedb6bc5056f3812f3ec02c74f9
https://doi.org/10.7717/peerj-cs.622
https://doi.org/10.7717/peerj-cs.622