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pro vyhledávání: '"Maliazurina Saad"'
Autor:
Maliazurina Saad, Ik Hyun Lee
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-12 (2020)
Abstract Background Clinical endpoint prediction remains challenging for health providers. Although predictors such as age, gender, and disease staging are of considerable predictive value, the accuracy often ranges between 60 and 80%. An accurate pr
Externí odkaz:
https://doaj.org/article/88b7f88cafe54298acf2505d4ede97f4
Autor:
Muhammad Aminu, Divya Yadav, Lingzhi Hong, Elliana Young, Paul Edelkamp, Maliazurina Saad, Morteza Salehjahromi, Pingjun Chen, Sheeba J. Sujit, Melissa M. Chen, Bradley Sabloff, Gregory Gladish, Patricia M. de Groot, Myrna C. B. Godoy, Tina Cascone, Natalie I. Vokes, Jianjun Zhang, Kristy K. Brock, Naval Daver, Scott E. Woodman, Hussein A. Tawbi, Ajay Sheshadri, J. Jack Lee, David Jaffray, D3CODE Team, Carol C. Wu, Caroline Chung, Jia Wu
Publikováno v:
Cancers, Vol 15, Iss 1, p 275 (2022)
Objectives: Cancer patients have worse outcomes from the COVID-19 infection and greater need for ventilator support and elevated mortality rates than the general population. However, previous artificial intelligence (AI) studies focused on patients w
Externí odkaz:
https://doaj.org/article/277644b1a91e41e29fbafb44be033647
Autor:
Maliazurina Saad, Shenghua He, Wade Thorstad, Hiram Gay, Daniel Barnett, Yujie Zhao, Su Ruan, Xiaowei Wang, Hua Li
Publikováno v:
IEEE Trans Radiat Plasma Med Sci
Predicting early in treatment whether a tumor is likely to be responsive is a difficult yet important task to support clinical decision-making. Studies have shown that multimodal biomarkers could provide complementary information and lead to more acc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7e828160f6d484553a815f4d05d8088
https://europepmc.org/articles/PMC9066560/
https://europepmc.org/articles/PMC9066560/
Publikováno v:
International Journal of Imaging Systems and Technology. 29:561-576
Autor:
Maliazurina Saad, Lee, Ik Hyun
Additional file 1 : Fig. 1. The survival distribution is plotted as KM curves using each of the proposed biomarkers as a risk factor. The comparison groups are given as patients clustered into solid-dominant (SD) and non-solid dominant (NSD) tumor gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc3b4e9e10a6da99accddc07beca4c11
Autor:
Tae-Sun Choi, Maliazurina Saad
Publikováno v:
Computers in Biology and Medicine. 91:222-230
Background Tumors are highly heterogeneous at the phenotypic, physiologic, and genomic levels. They are categorized in terms of a differentiated appearance under a microscope. Non-small-cell lung cancer tumors are categorized into three main subgroup
Autor:
Maliazurina Saad, Ik Hyun Lee
Publikováno v:
BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-12 (2020)
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-12 (2020)
BackgroundClinical endpoint prediction remains challenging for health providers. Although predictors such as age, gender, and disease staging are of considerable predictive value, the accuracy often ranges between 60 and 80%. An accurate prognosis as
Publikováno v:
Computer Methods and Programs in Biomedicine. 180:105028
Background and objective Mapping the architecture of the brain is essential for identifying the neural computations that affect behavior. Traditionally in histology, stained objects in tissue slices are hand-marked under a microscope in a manually in
Autor:
Maliazurina Saad
To date, developing a reliable mortality prediction model remains challenging. Although clinical predictors like age, gender and laboratory results are of considerable predictive value, the accuracy often ranges only between 60-80%. In this study, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a13e7025b5ae329b3918e3748904d0e6
https://doi.org/10.1101/341156
https://doi.org/10.1101/341156
Autor:
Maliazurina Saad
PurposeThe tendencies of non-small cell lung cancers (NSCLC) to be large-sized, irregularly shaped, and to grow against the surrounding structures can cause even expert clinicians to experience difficulty with accurate segmentation.MethodsAn automate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77b8304428bbbc7d10536566b4ad2f18