Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Eve Kazarian"'
Autor:
Mariam Aboian, Khaled Bousabarah, Eve Kazarian, Tal Zeevi, Wolfgang Holler, Sara Merkaj, Gabriel Cassinelli Petersen, Ryan Bahar, Harry Subramanian, Pranay Sunku, Elizabeth Schrickel, Jitendra Bhawnani, Mathew Zawalich, Amit Mahajan, Ajay Malhotra, Sam Payabvash, Irena Tocino, MingDe Lin, Malte Westerhoff
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
PurposePersonalized interpretation of medical images is critical for optimum patient care, but current tools available to physicians to perform quantitative analysis of patient’s medical images in real time are significantly limited. In this work,
Externí odkaz:
https://doaj.org/article/2bbcb1ba5ae54f2aabb31a9d5be51915
Autor:
Eve Kazarian, Asher Marks, Jin Cui, Armine Darbinyan, Elizabeth Tong, Sabine Mueller, Soonmee Cha, Mariam S. Aboian
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract We evaluate the topographic distribution of diffuse midline gliomas and hemispheric high-grade gliomas in children with respect to their normal gene expression patterns and pathologic driver mutation patterns. We identified 19 pediatric pati
Externí odkaz:
https://doaj.org/article/a038c37a85914ea29437336fc07bc4a3
Autor:
Ryan C. Bahar, Sara Merkaj, Gabriel I. Cassinelli Petersen, Niklas Tillmanns, Harry Subramanian, Waverly Rose Brim, Tal Zeevi, Lawrence Staib, Eve Kazarian, MingDe Lin, Khaled Bousabarah, Anita J. Huttner, Andrej Pala, Seyedmehdi Payabvash, Jana Ivanidze, Jin Cui, Ajay Malhotra, Mariam S. Aboian
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
ObjectivesTo systematically review, assess the reporting quality of, and discuss improvement opportunities for studies describing machine learning (ML) models for glioma grade prediction.MethodsThis study followed the Preferred Reporting Items for Sy
Externí odkaz:
https://doaj.org/article/0185748a65b042c88401ca7ad068272f
Autor:
Eve Kazarian, Asher Marks, Jin Cui, Armine Darbinyan, Elizabeth Tong, Sabine Mueller, Soonmee Cha, Mariam S. Aboian
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
Externí odkaz:
https://doaj.org/article/3c857996ba3f4289a35af026c97ea5d0
Autor:
Sandra Abi Fadel, Marc von Reppert, Eve Kazarian, E. Zeynep Erson Omay, Asher Marks, Nicolas Linder, Karl-Titus Hoffmann, Armine Darbinyan, Anita Huttner, Mariam S. Aboian
Publikováno v:
Neuroradiology. 65(1)
Pilomyxoid astrocytomas (PMA) are pediatric brain tumors predominantly located in the suprasellar region, third ventricle and posterior fossa, which are considered to be more clinically aggressive than pilocytic astrocytomas (PA). Another entity, int
Autor:
Tal Zeevi, Khaled Bousabarah, Harry Subramanian, Eve Kazarian, Jana Ivanidze, Jin Cui, Ajay Malhotra, Ming Lin, Ryan Bahar, W R Brim, Mariam Aboian, Sam Payabvash, Irena Tocino, Sara Merkaj
Publikováno v:
Neuro Oncol
PURPOSE Machine learning (ML) technologies have demonstrated highly accurate prediction of glioma grade, though it is unclear which methods and algorithms are superior. We have conducted a systematic review of the literature in order to identify the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d035368ad54a1b6dea4283269ae2428d
https://europepmc.org/articles/PMC8598529/
https://europepmc.org/articles/PMC8598529/
Autor:
Sabine Mueller, Soonmee Cha, Jin Cui, Mariam Aboian, Elizabeth Tong, Armine Darbinyan, Asher Marks, Eve Kazarian
Publikováno v:
Scientific reports, vol 11, iss 1
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports
We evaluate the topographic distribution of diffuse midline gliomas and hemispheric high-grade gliomas in children with respect to their normal gene expression patterns and pathologic driver mutation patterns. We identified 19 pediatric patients with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb283492605965d77a3e63ea0f587d40
https://escholarship.org/uc/item/509116f2
https://escholarship.org/uc/item/509116f2
NIMG-35. MACHINE LEARNING GLIOMA GRADE PREDICTION LITERATURE: A TRIPOD ANALYSIS OF REPORTING QUALITY
Autor:
Jin Cui, Ming Lin, Ajay Malhotra, Eve Kazarian, Jana Ivanidze, Sara Merkaj, Tal Zeevi, Mariam Aboian, W R Brim, Khaled Bousabarah, Harry Subramanian, Sam Payabvash, Ryan Bahar, Irena Tocino
Publikováno v:
Neuro Oncol
PURPOSE Reporting guidelines are crucial in model development studies to ensure the quality, transparency and objectivity of reporting. While machine learning (ML) models have proven themselves effective in predicting glioma grade, their potential us