Katie L. Ovens

16 papers Journal 7Unranked 9
YearRankTypeTitle / Venue / Authors
2025 — conf
Integrating Embedding Representations with Graph Convolutional Networks for Enhanced Sentiment Analysis.
ICCAI
Aref Motamedi, Katie L. Ovens
2025 J jnl
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.
J. Imaging Inform. Medicine
Farhad Maleki, Linda Moy, Reza Forghani, Tapotosh Ghosh, Katie L. Ovens, Steve Langer, Pouria Rouzrokh, Bardia Khosravi, Ali Ganjizadeh, Daniel I. Warren, Roxana Daneshjou, Mana Moassefi, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline
2025 — conf
Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net.
ICCAI
S. Sina Ziaee, Farhad Maleki, Katie L. Ovens
2024 — conf
Discovering Knowledge Embedded in Gene Set Databases: A Mathematical Modelling Approach.
ICCBB
Katie L. Ovens, Ebunoluwa Makinde, Samuel Horovatin, Elham Rezaei, Alan M. Rosenberg, Lingling Jin, Ian McQuillan, Anthony J. Kusalik, Farhad Maleki
2024 J jnl
Efficient Wheat Head Segmentation with Minimal Annotation: A Generative Approach.
J. Imaging
Jaden Myers, Keyhan Najafian, Farhad Maleki, Katie L. Ovens
2024 J jnl
Modified CycleGAN for the synthesization of samples for wheat head segmentation.
CoRR
Jaden Myers, Keyhan Najafian, Farhad Maleki, Katie L. Ovens
2024 J jnl
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models.
CoRR
Farhad Maleki, Linda Moy, Reza Forghani, Tapotosh Ghosh, Katie L. Ovens, Steve Langer, Pouria Rouzrokh, Bardia Khosravi, Ali Ganjizadeh, Daniel I. Warren, Roxana Daneshjou, Mana Moassefi, Atlas Haddadi Avval, Susan Sotardi, Neil A. Tenenholtz, Felipe Kitamura, Timothy Kline
2023 — conf
Deep Learning-Based Hierarchical Delineation of Kidneys, Tumors, and Cysts in CT Images.
KiTS@MICCAI
Andrew Heschl, Hosein Beheshtifard, Phuong Thao Nguyen, Tapotosh Ghosh, Katie L. Ovens, Farhad Maleki
2022 J jnl
Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls.
CoRR
Farhad Maleki, Katie L. Ovens, Rajiv Gupta, Caroline Reinhold, Alan Spatz, Reza Forghani
2021 — conf
A Deep Learning-Based Pipeline for Celiac Disease Diagnosis Using Histopathological Images.
CAIP (1)
Farhad Maleki, Kevin Cote, Keyhan Najafian, Katie L. Ovens, Yan Miao, Rita Zakarian, Caroline Reinhold, Reza Forghani, Peter Savadjiev, Zu-hua Gao
2021 J jnl
Juxtapose: a gene-embedding approach for comparing co-expression networks.
BMC Bioinform.
Katie L. Ovens, Farhad Maleki, B. Frank Eames, Ian McQuillan
2020 — conf
The impact of sample size and tissue type on the reproducibility of gene co-expression networks.
BCB
Katie L. Ovens, B. Frank Eames, Ian McQuillan
2019 — conf
Gene Set Databases: A Fountain of Knowledge or a Siren Call?
BCB
Farhad Maleki, Katie L. Ovens, Ian McQuillan, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2019 J jnl
Measuring consistency among gene set analysis methods: A systematic study.
J. Bioinform. Comput. Biol.
Farhad Maleki, Katie L. Ovens, Daniel J. Hogan, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2019 — conf
Method Choice in Gene Set Analysis Has Important Consequences for Analysis Outcome.
BIOINFORMATICS
Farhad Maleki, Katie L. Ovens, Elham Rezaei, Alan M. Rosenberg, Anthony J. Kusalik
2018 — conf
Sample Size and Reproducibility of Gene Set Analysis.
BIBM
Farhad Maleki, Katie L. Ovens, Ian McQuillan, Anthony J. Kusalik