Roselyne Tchoua

33 papers B 8Misc 3Journal 4Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Boosting 30-Day Emergency Department Readmission Predictions with BERT-Powered Community Health Worker Notes. BIOSTEC (4) Ankita Mishra, Charmi Patel, Naveen Kumar Reddy Veeramreddy, Yiyang Wang, John Mazzeo, Jamshid Sourati, Kelly McCabe, Roselyne Tchoua, Jacob Furst, Daniela Raicu
2025	B	`conf`	Enhancing Pulmonary Nodule Localization Based on Latent Representations. CBMS Charmi Patel, Yiyang Wang, Roselyne Tchoua, Thiruvarangan Ramaraj, Jacob D. Furst, Daniela Raicu
2025	—	`conf`	Leveraging Hidden Patterns in Open-Ended Community Health Workers' Notes to Improve Prediction of Patient Readmission. eScience Naveen Kumar Reddy Veeramreddy, Ankita Mishra, Navika Maglani, Sameer Shaik, Kelly McCabe, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua, Jamshid Sourati
2025	—	`conf`	Novel Perspective on Ensemble Clustering for Persistent Cluster Patterns: A Case Study in Disease Cluster Discovery. eScience Fernanda Cabral, Maria Alexandra Hubbard, Rudhvish Patel, Adeola Badmos, Daniela Raicu, Raj Shah, Roselyne Tchoua
2024	J	`jnl`	Biomedical heterogeneous data categorization and schema mapping toward data integration. Frontiers Big Data Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu, Michiel Schinkel, Hari Trivedi, Sameer K. Antani
2024	J	`jnl`	Leveraging Community Health Workers for Predicting Emergency Department Readmissions. Int. J. Semantic Comput. Nuvia Hernandez, Kate Karam, Nicole Baugh, Shilpa Musale, Aditya Patrick Moses, Daniela Raicu, Jacob D. Furst, Kelly McCabe, Roselyne Tchoua
2023	B	`conf`	Curriculum gDRO: Improving Lung Malignancy Classification through Robust Curriculum Task Learning. CBMS Arun Sivakumar, Yiyang Wang, Roselyne Tchoua, Thiruvarangan Ramaraj, Jacob Furst, Daniela Stan Raicu
2023	—	`conf`	Iterative K-means clustering for disease subtype discovery. Computer-Aided Diagnosis Katherine Aubert, Catherine Huber, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua
2023	—	`conf`	Leveraging Community Health Workers and Social Determinants of Health for Predicting Emergency Department Readmissions. TransAI Kate Karam, Kelly MacCabe, Roselyne Tchoua
2023	—	`conf`	Leveraging Interpretable Features and Clustering Agreements for Assistive Materials Discovery. TransAI Maria Alexandra Theodorescu, Jacob D. Furst, Daniela Stan Raicu, Roselyne Tchoua
2023	Misc	`conf`	Multiclass Classification of Software Vulnerabilities with Deep Learning. ICMLC Crystal Contreras, Hristina Dokic, Zhen Huang, Daniela Stan Raicu, Jacob Furst, Roselyne Tchoua
2023	—	`conf`	No nodule left behind: evaluating lung nodule malignancy classification with different stratification schemes. Computer-Aided Diagnosis Thomas Zeng, Elias Furst, Yiyang Wang, Roselyne Tchoua, Jacob D. Furst, Daniela Raicu
2022	J	`jnl`	CompNet: A Designated Model to Handle Combinations of Images and Designed features. CoRR Bowen Qiu, Daniela Raicu, Jacob Furst, Roselyne Tchoua
2022	—	`conf`	Contextualizing Lung Nodule Malignancy Predictions with Easy vs. Hard Image Classification. TransAI Edward Xu, Thiruvarangan Ramaraj, Roselyne Tchoua, Jacob Furst, Daniela Raicu
2022	—	`conf`	Ensuring AI For Science is Science: Making Randomness Portable. AI4S Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
2022	B	`conf`	Failure Sources in Machine Learning for Medicine - A Study. e-Science Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
2022	—	`conf`	Human-in-the-loop deep learning retinal image classification with customized loss function. Computer-Aided Diagnosis Suhev Shakya, Mariana Vasquez, Yiyang Wang, Roselyne Tchoua, Jacob Furst, Daniela Raicu
2022	B	`conf`	Interactive deep learning for explainable retinal disease classification. Image Processing Mariana Vasquez, Suhev Shakya, Ian Wang, Jacob Furst, Roselyne Tchoua, Daniela Raicu
2022	—	`conf`	Measuring Reproduciblity of Machine Learning Methods for Medical Diagnosis. TransAI Hana Ahmed, Roselyne Tchoua, Jay F. Lofstead
2022	—	`conf`	Similarity-based uncertainty scores for computer-aided diagnosis. Computer-Aided Diagnosis Claire Weissman, Lilly Roelofs, Jacob Furst, Daniela Stan Raicu, Roselyne Tchoua
2022	Misc	`conf`	Similarity-based uncertainty scores for interpretable deep learning in scientific applications. SAC Lilly Roelofs, Claire Weissman, Daniela Raicu, Jacob Furst, Roselyne Tchoua
2022	B	`conf`	Text Summarization towards Scientific Information Extraction. e-Science Abigail Keller, Jacob Furst, Daniela Raicu, Peter M. Hastings, Roselyne Tchoua
2021	—	`conf`	Ensemble Labeling Towards Scientific Information Extraction (ELSIE). ICCS (1) Erin Murphy, Alexander Rasin, Jacob Furst, Daniela Raicu, Roselyne Tchoua
2021	B	`conf`	Ensemble Labeling towards Scientific Information Extraction (ELSIE) - Blob Extraction. e-Science Erin Murphy, Alexander Rasin, Jacob Furst, Daniela Raicu, Roselyne Tchoua
2020	B	`conf`	Enhancing Recall Using Data Cleaning for Biomedical Big Data. CBMS Priya Deshpande, Alexander Rasin, Roselyne Tchoua, Jacob Furst, Daniela Raicu, Sameer K. Antani
2020	—	`conf`	Learning Latent Spiculated Features for Lung Nodule Characterization. EMBC Bowen Qiu, Jacob Furst, Alexander Rasin, Roselyne Tchoua, Daniela Raicu
2020	—	`conf`	SciNER: Extracting Named Entities from Scientific Literature. ICCS (2) Zhi Hong, Roselyne Tchoua, Kyle Chard, Ian T. Foster
2019	—	`conf`	Active Learning Yields Better Training Data for Scientific Named Entity Recognition. eScience Roselyne Tchoua, Aswathy Ajith, Zhi Hong, Logan T. Ward, Kyle Chard, Debra Audus, Shrayesh Patel, Juan de Pablo, Ian T. Foster
2016	Misc	`conf`	A Hybrid Human-computer Approach to the Extraction of Scientific Facts from the Literature. ICCS Roselyne Tchoua, Kyle Chard, Debra Audus, Jian Qin, Juan de Pablo, Ian T. Foster
2014	J	`jnl`	Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks. Concurr. Comput. Pract. Exp. 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
2013	B	`conf`	ADIOS Visualization Schema: A First Step Towards Improving Interdisciplinary Collaboration in High Performance Computing. e-Science Roselyne Tchoua, Jong Youl Choi, Scott Klasky, Qing Liu, Jeremy Logan, Kenneth Moreland, Jingqing Mu, Manish Parashar, Norbert Podhorszki, David Pugmire, Matthew Wolf
2012	—	`conf`	Collaborative monitoring and visualization of HPC data. CTS Roselyne Tchoua, Hasan Abbasi, Scott Klasky, Qing Liu, Norbert Podhorszki, David Pugmire, Yuan Tian, Matthew Wolf
2010	—	`conf`	Collaborative monitoring and analysis for simulation scientists. CTS Roselyne Tchoua, Scott Klasky, Norbert Podhorszki, Brad Grimm, Ayla Khan, Emanuele Santos, Cláudio T. Silva, Pierre Mouallem, Mladen A. Vouk