Roselyne Tchoua

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 22

Top Topics

Information Extraction

Multiclass Classification

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Publications

Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu, Michiel Schinkel, Hari Trivedi, Sameer K. Antani
Biomedical heterogeneous data categorization and schema mapping toward data integration. Frontiers Big Data 6 (2024)
Katherine Aubert, Catherine Huber, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua
Iterative K-means clustering for disease subtype discovery. Medical Imaging: Computer-Aided Diagnosis (2023)
Thomas Zeng, Elias Furst, Yiyang Wang, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu
No nodule left behind: evaluating lung nodule malignancy classification with different stratification schemes. Medical Imaging: Computer-Aided Diagnosis (2023)
Arun Sivakumar, Yiyang Wang, Roselyne Tchoua, Thiruvarangan Ramaraj, Jacob Furst, Daniela Stan Raicu
Curriculum gDRO: Improving Lung Malignancy Classification through Robust Curriculum Task Learning. CBMS (2023)
Crystal Contreras, Hristina Dokic, Zhen Huang, Daniela Stan Raicu, Jacob Furst, Roselyne Tchoua
Multiclass Classification of Software Vulnerabilities with Deep Learning. ICMLC (2023)
Bowen Qiu, Daniela Raicu, Jacob Furst, Roselyne Tchoua
CompNet: A Designated Model to Handle Combinations of Images and Designed features. CoRR (2022)
Mariana Vasquez, Suhev Shakya, Ian Wang, Jacob Furst, Roselyne Tchoua, Daniela Raicu
Interactive deep learning for explainable retinal disease classification. Medical Imaging: Image Processing (2022)
Abigail Keller, Jacob Furst, Daniela Raicu, Peter Hastings, Roselyne Tchoua
Text Summarization towards Scientific Information Extraction. e-Science (2022)
Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
Measuring Reproduciblity of Machine Learning Methods for Medical Diagnosis. TransAI (2022)
Lilly Roelofs, Claire Weissman, Daniela Raicu, Jacob Furst, Roselyne Tchoua
Similarity-based uncertainty scores for interpretable deep learning in scientific applications. SAC (2022)
Suhev Shakya, Mariana Vasquez, Yiyang Wang, Roselyne Tchoua, Jacob Furst, Daniela Raicu
Human-in-the-loop deep learning retinal image classification with customized loss function. Medical Imaging: Computer-Aided Diagnosis (2022)
Edward Xu, Thiruvarangan Ramaraj, Roselyne Tchoua, Jacob Furst, Daniela Raicu
Contextualizing Lung Nodule Malignancy Predictions with Easy vs. Hard Image Classification. TransAI (2022)
Claire Weissman, Lilly Roelofs, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua
Similarity-based uncertainty scores for computer-aided diagnosis. Medical Imaging: Computer-Aided Diagnosis (2022)
Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
Failure Sources in Machine Learning for Medicine - A Study. e-Science (2022)
Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
Ensuring AI For Science is Science: Making Randomness Portable. AI4S (2022)
Erin Murphy, Alexander Rasin, Jacob D. Furst, Daniela Raicu, Roselyne Tchoua
Ensemble Labeling towards Scientific Information Extraction (ELSIE) - Blob Extraction. e-Science (2021)
Erin Murphy, Alexander Rasin, Jacob D. Furst, Daniela Raicu, Roselyne Tchoua
Ensemble Labeling Towards Scientific Information Extraction (ELSIE). ICCS (1) (2021)
Zhi Hong, Roselyne Tchoua, Kyle Chard, Ian T. Foster
SciNER: Extracting Named Entities from Scientific Literature. ICCS (2) (2020)
Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu, Sameer K. Antani
Enhancing Recall Using Data Cleaning for Biomedical Big Data. CBMS (2020)
Bowen Qiu, Jacob D. Furst, Alexander Rasin, Roselyne Tchoua, Daniela Raicu
Learning Latent Spiculated Features for Lung Nodule Characterization. EMBC (2020)
Roselyne Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Debra Audus, Shrayesh Patel, Juan de Pablo, Ian T. Foster
Active Learning Yields Better Training Data for Scientific Named Entity Recognition. eScience (2019)
Roselyne Tchoua, Kyle Chard, Debra Audus, Jian Qin, Juan de Pablo, Ian T. Foster
A Hybrid Human-computer Approach to the Extraction of Scientific Facts from the Literature. ICCS (2016)
Qing Liu, Jeremy Logan, Yuan Tian, Hasan Abbasi, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, Roselyne Tchoua, Jay F. Lofstead, Ron A. Oldfield, Manish Parashar, Nagiza F. Samatova, Karsten Schwan, Arie Shoshani, Matthew Wolf, Kesheng Wu, Weikuan Yu
Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurr. Comput. Pract. Exp. 26 (7) (2014)
Roselyne Tchoua, Jong Youl Choi, Scott Klasky, Qing Liu, Jeremy Logan, Kenneth Moreland, Jingqing Mu, Manish Parashar, Norbert Podhorszki, David Pugmire, Matthew Wolf
ADIOS Visualization Schema: A First Step Towards Improving Interdisciplinary Collaboration in High Performance Computing. e-Science (2013)
Roselyne Tchoua, Hasan Abbasi, Scott Klasky, Qing Liu, Norbert Podhorszki, David Pugmire, Yuan Tian, Matthew Wolf
Collaborative monitoring and visualization of HPC data. CTS (2012)
Roselyne Tchoua, Scott Klasky, Norbert Podhorszki, Brad Grimm, Ayla Khan, Emanuele Santos, Cláudio T. Silva, Pierre Mouallem, Mladen A. Vouk
Collaborative monitoring and analysis for simulation scientists. CTS (2010)