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2020 – today
- 2024
[j33]Alina Peluso
, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd-Yusof, Tanmoy Bhattacharya, Adam Spannaus, Noah Schaefferkoetter, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Stephen M. Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Shang Gao:
Deep learning uncertainty quantification for clinical text classification. J. Biomed. Informatics 149: 104576 (2024)- [j32]Hong-Jun Yoon, Hilda B. Klasky, Andrew E. Blanchard, James Blair Christian, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
Development of message passing-based graph convolutional networks for classifying cancer pathology reports. BMC Medical Informatics Decis. Mak. 24-S(5): 262 (2024) - [c79]Georgia D. Tourassi:
Powering Progress in Leadership Computing in the Era of Generative AI and Energy Constraints. SIGSIM-PADS 2024: 1 - [c78]Adam Spannaus, Heidi A. Hanson, Georgia D. Tourassi, Lynne Penberthy:
Topological Interpretability for Deep Learning. PASC 2024: 21:1-21:11 - [i5]Prasanna Date, Dong Jun Woun, Kathleen E. Hamilton, Eduardo Antonio Coello Pérez, Mayanka Chandra Shekar, Francisco Rios, John Gounley, In-Saeng Suh, Travis S. Humble, Georgia D. Tourassi:
Adiabatic Quantum Support Vector Machines. CoRR abs/2401.12485 (2024) - 2023
- [j31]Sergio Cerutti, Björn M. Eskofier, Georgia D. Tourassi:
Guest Editorial Advancing Biomedical Discovery and Healthcare Delivery Through Digital Technology. IEEE J. Biomed. Health Informatics 27(6): 2656-2659 (2023) - [j30]Junqi Yin, Sajal Dash, John Gounley, Feiyi Wang, Georgia D. Tourassi:
Evaluation of pre-training large language models on leadership-class supercomputers. J. Supercomput. 79(18): 20747-20768 (2023) - [c77]Georgia D. Tourassi:
Computational Medicine in the Exascale Computing Era: Applications at the Oak Ridge Leadership Computing Facility. JVA 2023: 75-79 - [c76]Aristeidis Tsaris, Joshua Romero, Thorsten Kurth, Jacob D. Hinkle, Hong-Jun Yoon, Feiyi Wang, Sajal Dash, Georgia D. Tourassi:
Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks. PASC 2023: 2:1-2:11 - [c75]Kathleen E. Hamilton, Mayanka Chandra Shekar, John Gounley, Dhanvi Bharadwaj, Prasanna Date, Eduardo Antonio Coello Pérez, In-Saeng Suh, Georgia D. Tourassi:
Characterizing Quantum Classifier Utility in Natural Language Processing Workflows. QCE 2023: 369-370 - [i4]Adam Spannaus, Heidi A. Hanson, Lynne Penberthy, Georgia D. Tourassi:
Topological Interpretability for Deep-Learning. CoRR abs/2305.08642 (2023) - 2022
- [j29]Kevin De Angeli, Shang Gao, Ioana Danciu, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Stephen M. Schwartz, Charles Wiggins, Mark Damesyn, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi, Hong-Jun Yoon:
Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types. J. Biomed. Informatics 125: 103957 (2022) - [j28]Andrew E. Blanchard, Shang Gao, Hong-Jun Yoon, James Blair Christian, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Stephen M. Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification. IEEE J. Biomed. Health Informatics 26(6): 2796-2803 (2022) - 2021
- [j27]Kevin De Angeli, Shang Gao, Mohammed M. Alawad, Hong-Jun Yoon, Noah Schaefferkoetter, Xiao-Cheng Wu, Eric B. Durbin, Jennifer A. Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
Deep active learning for classifying cancer pathology reports. BMC Bioinform. 22(1): 113 (2021) - [j26]Mohammed M. Alawad, Hong-Jun Yoon, Shang Gao, Brent J. Mumphrey, Xiao-Cheng Wu, Eric B. Durbin, Jong Cheol Jeong, Isaac Hands, David Rust, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
Privacy-Preserving Deep Learning NLP Models for Cancer Registries. IEEE Trans. Emerg. Top. Comput. 9(3): 1219-1230 (2021) - [j25]Shang Gao, Mohammed M. Alawad, M. Todd Young, John Gounley, Noah Schaefferkoetter, Hong-Jun Yoon, Xiao-Cheng Wu, Eric B. Durbin, Jennifer A. Doherty, Antoinette Stroup, Linda Coyle, Georgia D. Tourassi:
Limitations of Transformers on Clinical Text Classification. IEEE J. Biomed. Health Informatics 25(9): 3596-3607 (2021) - [i3]Mohammed M. Alawad, Shang Gao, Mayanka Chandra Shekar, S. M. Shamimul Hasan, James Blair Christian, Xiao-Cheng Wu, Eric B. Durbin, Jennifer A. Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping. CoRR abs/2101.01337 (2021) - 2020
- [j24]Mohammed M. Alawad, Shang Gao, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Lynne Penberthy, Brent J. Mumphrey, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi:
Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks. J. Am. Medical Informatics Assoc. 27(1): 89-98 (2020) - [j23]Hong-Jun Yoon, Hilda B. Klasky, John P. Gounley, Mohammed M. Alawad, Shang Gao, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Linda Coyle, Lynne Penberthy, James Blair Christian, Georgia D. Tourassi:
Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. J. Biomed. Informatics 110: 103564 (2020) - [j22]S. M. Shamimul Hasan, Donna R. Rivera, Xiao-Cheng Wu, Eric B. Durbin, James Blair Christian, Georgia D. Tourassi:
Knowledge Graph-Enabled Cancer Data Analytics. IEEE J. Biomed. Health Informatics 24(7): 1952-1967 (2020) - [c74]Hong-Jun Yoon, Hilda B. Klasky, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer A. Doherty, Linda Coyle, Lynne Penberthy, Christopher B. Stanley, James Blair Christian, Georgia D. Tourassi:
Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles. Poly/DMAH@VLDB 2020: 87-99 - [i2]Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Kumkum Ganguly, Gopinath Chennupati, Sunil Thulasidasan, Nicolas W. Hengartner, Brent J. Mumphrey, Eric B. Durbin, Jennifer A. Doherty, Mireille Lemieux, Noah Schaefferkoetter, Georgia D. Tourassi, Linda Coyle, Lynne Penberthy, Benjamin McMahon, Tanmoy Bhattacharya:
Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports. CoRR abs/2009.05094 (2020)
2010 – 2019
- 2019
- [j21]Shang Gao, John X. Qiu, Mohammed M. Alawad, Jacob D. Hinkle, Noah Schaefferkoetter, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Lynne Penberthy, Xiao-Cheng Wu, Linda Coyle, Georgia D. Tourassi, Arvind Ramanathan:
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - [j20]Shuayb Zarar, Georgia D. Tourassi, Chris D. Nugent:
Guest Editorial: AI Enabled Connected Health Informatics. IEEE J. Biomed. Health Informatics 23(3): 921-922 (2019) - [c73]Abhishek Kumar Dubey, Jacob D. Hinkle, James Blair Christian, Georgia D. Tourassi:
Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters. BCB 2019: 320-327 - [c72]Mohammed M. Alawad, Shang Gao, John X. Qiu, Noah Schaefferkoetter, Jacob D. Hinkle, Hong-Jun Yoon, James Blair Christian, Xiao-Cheng Wu, Eric B. Durbin, Jong Cheol Jeong, Isaac Hands, David Rust, Georgia D. Tourassi:
Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology Reports. BHI 2019: 1-4 - [c71]Abhishek Kumar Dubey, Hong-Jun Yoon, Georgia D. Tourassi:
Inverse Regression for Extraction of Tumor Site from Cancer Pathology Reports. BHI 2019: 1-4 - [c70]S. M. Shamimul Hasan, Donna R. Rivera, Xiao-Cheng Wu, James Blair Christian, Georgia D. Tourassi:
A Knowledge Graph Approach for the Secondary Use of Cancer Registry Data. BHI 2019: 1-4 - [c69]John X. Qiu, Shang Gao, Mohammed M. Alawad, Noah Schaefferkoetter, Folami Alamudun, Hong-Jun Yoon, Xiao-Cheng Wu, Georgia D. Tourassi:
Semi-Supervised Information Extraction for Cancer Pathology Reports. BHI 2019: 1-4 - [c68]Hong-Jun Yoon, John Gounley, Shang Gao, Mohammed M. Alawad, Arvind Ramanathan, Georgia D. Tourassi:
Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC. BHI 2019: 1-4 - [c67]Hong-Jun Yoon, John Gounley, M. Todd Young, Georgia D. Tourassi:
Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. IEEE BigData 2019: 4561-4564 - [c66]Mohammed M. Alawad, Shang Gao, Xiao-Cheng Wu, Eric B. Durbin, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi:
Adversarial Training for Privacy-Preserving Deep Learning Model Distribution. IEEE BigData 2019: 5705-5710 - [c65]Hong-Jun Yoon, John X. Qiu, James Blair Christian, Jacob D. Hinkle, Folami Alamudun, Georgia D. Tourassi:
Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks. INNSBDDL 2019: 89-98 - [c64]Mohammed M. Alawad, Georgia D. Tourassi:
Computationally Efficient Learning of Quality Controlled Word Embeddings for Natural Language Processing. ISVLSI 2019: 134-139 - [c63]Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle:
Computer-aided detection using non-convolutional neural network Gaussian processes. Computer-Aided Diagnosis 2019: 109503N - 2018
- [j19]Nicolas W. Hengartner, Leticia Cuellar, Xiao-Cheng Wu, Georgia D. Tourassi, John X. Qiu, James Blair Christian, Tanmoy Bhattacharya:
CAT: computer aided triage improving upon the Bayes risk through ε-refusal triage rules. BMC Bioinform. 19-S(18): 3-8 (2018) - [j18]John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, James Blair Christian, Arvind Ramanathan, Xiao-Cheng Wu, Paul A. Fearn, Georgia D. Tourassi:
Scalable deep text comprehension for Cancer surveillance on high-performance computing. BMC Bioinform. 19-S(18): 99-110 (2018) - [j17]Shang Gao, Michael T. Young, John X. Qiu, Hong-Jun Yoon, James Blair Christian, Paul A. Fearn, Georgia D. Tourassi, Arvind Ramanathan:
Hierarchical attention networks for information extraction from cancer pathology reports. J. Am. Medical Informatics Assoc. 25(3): 321-330 (2018) - [j16]John X. Qiu, Hong-Jun Yoon, Paul A. Fearn, Georgia D. Tourassi:
Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports. IEEE J. Biomed. Health Informatics 22(1): 244-251 (2018) - [c62]Mohammed M. Alawad, Hong-Jun Yoon, Georgia D. Tourassi:
Coarse-to-fine multi-task training of convolutional neural networks for automated information extraction from cancer pathology reports. BHI 2018: 218-221 - [c61]Hong-Jun Yoon, Sarah Robinson, James Blair Christian, John X. Qiu, Georgia D. Tourassi:
Filter pruning of Convolutional Neural Networks for text classification: A case study of cancer pathology report comprehension. BHI 2018: 345-348 - [c60]Mohammed M. Alawad, S. M. Shamimul Hasan, James Blair Christian, Georgia D. Tourassi:
Retrofitting Word Embeddings with the UMLS Metathesaurus for Clinical Information Extraction. IEEE BigData 2018: 2838-2846 - [c59]Hong-Jun Yoon, Arvind Ramanathan, Folami Alamudun, Georgia D. Tourassi:
Deep radiogenomics for predicting clinical phenotypes in invasive breast cancer. IWBI 2018: 107181H - [c58]Shang Gao, Arvind Ramanathan, Georgia D. Tourassi:
Hierarchical Convolutional Attention Networks for Text Classification. Rep4NLP@ACL 2018: 11-23 - [i1]Edmon Begoli, Jim Brase, Bambi DeLaRosa, Penelope Jones, Dimitri Kusnezov, Jason Paragas, Rick Stevens, Frederick H. Streitz, Georgia D. Tourassi:
Precision Medicine as an Accelerator for Next Generation Cognitive Supercomputing. CoRR abs/1804.11002 (2018) - 2017
- [c57]Jessica A. Boten, Donna R. Rivera, Madhumita Myneni, Georgia D. Tourassi, Tanmoy Bhattacharya, Ana Paula de Oliveira Sales, Thomas S. Brettin, Paul A. Fearn, Lynne Penberthy:
Leveraging Large-Scale Computing for Population Information Integration, Analysis, and Modeling. AMIA 2017 - [c56]Hong-Jun Yoon, Larry Roberts, Georgia D. Tourassi:
Automated histologic grading from free-text pathology reports using graph-of-words features and machine learning. BHI 2017: 369-372 - [c55]Mohammed M. Alawad, Hong-Jun Yoon, Georgia D. Tourassi:
Energy efficient stochastic-based deep spiking neural networks for sparse datasets. IEEE BigData 2017: 311-318 - [c54]Georgia D. Tourassi:
Deep learning enabled national cancer surveillance. IEEE BigData 2017: 3982-3983 - [c53]Folami T. Alamudun, Tracy Hammond, Hong-Jun Yoon, Georgia D. Tourassi:
Geometry and Gesture-Based Features from Saccadic Eye-Movement as a Biometric in Radiology. HCI (14) 2017: 123-138 - 2016
- [j15]Georgia D. Tourassi, Hong-Jun Yoon, Songhua Xu, Xuesong Han:
The utility of web mining for epidemiological research: studying the association between parity and cancer risk. J. Am. Medical Informatics Assoc. 23(3): 588-595 (2016) - [j14]Georgia D. Tourassi, Hong-Jun Yoon, Songhua Xu:
A novel web informatics approach for automated surveillance of cancer mortality trends. J. Biomed. Informatics 61: 110-118 (2016) - [c52]Hong-Jun Yoon, Georgia D. Tourassi:
Investigating the association between sociodemographic factors and lung cancer risk using cyber informatics. BHI 2016: 557-560 - [c51]Hong-Jun Yoon, Songhua Xu, Georgia D. Tourassi:
Predicting lung cancer incidence from air pollution exposures using shapelet-based time series analysis. BHI 2016: 565-568 - [c50]Hong-Jun Yoon, Arvind Ramanathan, Georgia D. Tourassi:
Multi-task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports. INNS Conference on Big Data 2016: 195-204 - [c49]Folami Alamudun, Hong-Jun Yoon, Tracy Hammond, Kathy Hudson, Garnetta Morin-Ducote, Georgia D. Tourassi:
Shapelet analysis of pupil dilation for modeling visuo-cognitive behavior in screening mammography. Image Perception, Observer Performance, and Technology Assessment 2016: 97870M - [e2]Georgia D. Tourassi, Samuel G. Armato III:
Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February - 3 March 2016. SPIE Proceedings 9785, SPIE 2016, ISBN 9781510600201 [contents] - 2015
- [c48]Yang Liu, Songhua Xu, Georgia D. Tourassi:
Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment. SBP 2015: 121-130 - [c47]Hong-Jun Yoon, Georgia D. Tourassi, Songhua Xu:
Residential Mobility and Lung Cancer Risk: Data-Driven Exploration Using Internet Sources. SBP 2015: 464-469 - [e1]Lubomir M. Hadjiiski, Georgia D. Tourassi:
Medical Imaging 2015: Computer-Aided Diagnosis, Orlando, Florida, United States, 21-26 February 2015. SPIE Proceedings 9414, SPIE 2015, ISBN 9781628415049 [contents] - 2014
- [j13]Songhua Xu, Hong-Jun Yoon, Georgia D. Tourassi:
A user-oriented web crawler for selectively acquiring online content in e-health research. Bioinform. 30(1): 104-114 (2014) - [c46]Yang Liu, Songhua Xu, Hong-Jun Yoon, Georgia D. Tourassi:
Extracting Patient Demographics and Personal Medical Information from Online Health Forums. AMIA 2014 - 2013
- [j12]Georgia D. Tourassi, Sophie Voisin, Vincent C. Paquit, Elizabeth A. Krupinski:
Research and applications: Investigating the link between radiologists' gaze, diagnostic decision, and image content. J. Am. Medical Informatics Assoc. 20(6): 1067-1075 (2013) - [c45]Alex C. Williams, Austin Hitt, Sophie Voisin, Georgia D. Tourassi:
Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening. Computer-Aided Diagnosis 2013: 86701A - 2012
- [j11]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi:
The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support. Neural Networks 25: 141-145 (2012) - [c44]Songhua Xu, Georgia D. Tourassi:
A novel local learning based approach with application to breast cancer diagnosis. Computer-Aided Diagnosis 2012: 83151Y - 2011
- [j10]Maciej A. Mazurowski, Joseph Y. Lo, Brian P. Harrawood, Georgia D. Tourassi:
Mutual information-based template matching scheme for detection of breast masses: From mammography to digital breast tomosynthesis. J. Biomed. Informatics 44(5): 815-823 (2011) - 2010
- [c43]Georgia D. Tourassi, Maciej A. Mazurowski, Elizabeth A. Krupinski:
Perception-driven IT-CADe analysis for the detection of masses in screening mammography: initial investigation. Computer-Aided Diagnosis 2010: 762406
2000 – 2009
- 2009
- [c42]Jordan M. Malof, Maciej A. Mazurowski, Georgia D. Tourassi:
The effect of class imbalance on case selection for case-based classifiers, with emphasis on computer-aided diagnosis systems. IJCNN 2009: 1975-1980 - [c41]Maciej A. Mazurowski, Georgia D. Tourassi:
Evaluating classifiers: Relation between area under the receiver operator characteristic curve and overall accuracy. IJCNN 2009: 2045-2049 - [c40]Maciej A. Mazurowski, Jordan M. Malof, Jacek M. Zurada, Georgia D. Tourassi:
A comparative study of database reduction methods for case-based computer-aided detection systems: preliminary results. Computer-Aided Diagnosis 2009: 72600F - [c39]Georgia D. Tourassi, Brian P. Harrawood:
Information-theoretic CAD system in mammography: improved mass detection by incorporating a Gaussian saliency map. Computer-Aided Diagnosis 2009: 726017 - [c38]Maciej A. Mazurowski, Georgia D. Tourassi:
Relational representation for improved decisions with an information-theoretic CADe system: initial experience. Computer-Aided Diagnosis 2009: 726018 - 2008
- [j9]Maciej A. Mazurowski, Piotr A. Habas, Jacek M. Zurada, Joseph Y. Lo, Jay A. Baker, Georgia D. Tourassi:
Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance. Neural Networks 21(2-3): 427-436 (2008) - [c37]Swatee Singh, Georgia D. Tourassi, Joseph Y. Lo:
Effect of Similarity Metrics and ROI Sizes in Featureless Computer Aided Detection of Breast Masses in Tomosynthesis. Digital Mammography / IWDM 2008: 286-291 - [c36]Georgia D. Tourassi, Amy C. Sharma, Swatee Singh, Robert S. Saunders, Joseph Y. Lo, Ehsan Samei, Brian P. Harrawood:
Knowledge Transfer across Breast Cancer Screening Modalities: A Pilot Study Using an Information-Theoretic CADe System for Mass Detection. Digital Mammography / IWDM 2008: 292-298 - [c35]Piotr A. Habas, Jacek M. Zurada, Georgia D. Tourassi:
Case-Specific Reliability Assessment for Improved False Positive Reduction with an Information-Theoretic CAD System. Digital Mammography / IWDM 2008: 329-335 - [c34]Maciej A. Mazurowski, Jacek M. Zurada, Georgia D. Tourassi:
Reliability Assessment of Ensemble Classifiers: Application in Mammography. Digital Mammography / IWDM 2008: 366-370 - [c33]Maciej A. Mazurowski, Jacek M. Zurada, Georgia D. Tourassi:
Database decomposition of a knowledge-based CAD system in mammography: an ensemble approach to improve detection. Computer-Aided Diagnosis 2008: 69151K - [c32]Swatee Singh, Georgia D. Tourassi, Amarpreet S. Chawla, Robert S. Saunders, Ehsan Samei, Joseph Y. Lo:
Computer-aided detection of breast masses in tomosynthesis reconstructed volumes using information-theoretic similarity measures. Computer-Aided Diagnosis 2008: 691505 - [c31]Robert C. Ike, Swatee Singh, Brian P. Harrawood, Georgia D. Tourassi:
Effect of ROI size on the performance of an information-theoretic CAD system in mammography: multi-size fusion analysis. Computer-Aided Diagnosis 2008: 691527 - 2007
- [j8]Nevine H. Eltonsy, Georgia D. Tourassi, Adel Said Elmaghraby:
A Concentric Morphology Model for the Detection of Masses in Mammography. IEEE Trans. Medical Imaging 26(6): 880-889 (2007) - [c30]Maciej A. Mazurowski, Piotr A. Habas, Georgia D. Tourassi, Jacek M. Zurada:
Case-base reduction for a computer assisted breast cancer detection system using genetic algorithms. IEEE Congress on Evolutionary Computation 2007: 600-605 - [c29]Nevine H. Eltonsy, Adel Said Elmaghraby, Georgia D. Tourassi:
Bilateral Breast Volume Asymmetry in Screening Mammograms as a Potential Marker of Breast Cancer: Preliminary Experience. ICIP (5) 2007: 5-8 - [c28]Georgia D. Tourassi, Jonathan L. Jesneck, Maciej A. Mazurowski, Piotr A. Habas:
Stacked Generalization in Computer-Assisted Decision Systems: Empirical Comparison of Data Handling Schemes. IJCNN 2007: 1343-1347 - [c27]Maciej A. Mazurowski, Piotr A. Habas, Georgia D. Tourassi, Jacek M. Zurada:
Impact of Low Class Prevalence on the Performance Evaluation of Neural Network Based Classifiers: Experimental Study in the Context of Computer-Assisted Medical Diagnosis. IJCNN 2007: 2005-2009 - [c26]Piotr A. Habas, Jacek M. Zurada, Adel Said Elmaghraby, Georgia D. Tourassi:
Particle swarm optimization of neural network CAD systems with clinically relevant objectives. Computer-Aided Diagnosis 2007: 65140M - [c25]Georgia D. Tourassi, Brian P. Harrawood, Carey E. Floyd Jr.:
Cross-digitizer robustness of a knowledge-based CAD system for mass detection in mammograms. Computer-Aided Diagnosis 2007: 65141Y - [c24]Georgia D. Tourassi, Anna O. Bilska-Wolak, Piotr A. Habas, Carey E. Floyd Jr.:
Incorporation of a multiscale texture-based approach to mutual information matching for improved knowledge-based detection of masses in screening mammograms. Computer-Aided Diagnosis 2007: 651403 - [c23]Nevine H. Eltonsy, Georgia D. Tourassi, Adel Said Elmaghraby:
Contribution of Haar wavelets and MPEG-7 textural features for false positive reduction in a CAD system for the detection of masses in mammograms. Computer-Aided Diagnosis 2007: 651404 - [c22]Swatee Singh, Georgia D. Tourassi, Joseph Y. Lo:
Breast mass detection in tomosynthesis projection images using information-theoretic similarity measures. Computer-Aided Diagnosis 2007: 651415 - 2006
- [j7]Mia K. Markey, Georgia D. Tourassi, Michael Margolis, David M. DeLong:
Impact of missing data in evaluating artificial neural networks trained on complete data. Comput. Biol. Medicine 36(5): 516-525 (2006) - [c21]Nevine H. Eltonsy, Georgia D. Tourassi, Aleksey Fadeev, Adel Said Elmaghraby:
Significance of MPEG-7 Textural Features for Improved Mass Detection in Mammography. EMBC 2006: 4779-4782 - [c20]Piotr A. Habas, Jacek M. Zurada, Adel Said Elmaghraby, Georgia D. Tourassi:
Probabilistic Framework for Reliability Analysis of Information-Theoretic CAD Systems in Mammography. EMBC 2006: 6113-6116 - [c19]Piotr A. Habas, Jacek M. Zurada, Adel Said Elmaghraby, Georgia D. Tourassi:
Confidence-based stratification of CAD recommendations with application to breast cancer detection. Image Processing 2006: 61445G - 2005
- [j6]Mark P. Wachowiak, Renata Smolíkova, Georgia D. Tourassi, Adel Said Elmaghraby:
Estimation of generalized entropies with sample spacing. Pattern Anal. Appl. 8(1-2): 95-101 (2005) - [j5]Mark P. Wachowiak, Renata Smolíkova, Georgia D. Tourassi, Adel Said Elmaghraby:
Estimation of generalized entropies with sample spacing. Pattern Anal. Appl. 8(3): 303-303 (2005) - [c18]Aleksey Fadeev, Nevine H. Eltonsy, Georgia D. Tourassi, Robert Martin, Adel Elmaghraby:
Adapted morphing model for 3D volume reconstruction applied to abdominal CT images. Image-Guided Procedures 2005 - [c17]Nevine H. Eltonsy, Georgia D. Tourassi, Piotr A. Habas, Adel Said Elmaghraby:
DNA: directional neighborhood analysis for detection of breast masses in screening mammograms. Image Processing 2005 - [c16]Piotr A. Habas, Georgia D. Tourassi, Nevine H. Eltonsy, Adel Said Elmaghraby, Jacek M. Zurada:
A novel technique for assessing the case-specific reliability of decisions made by CAD tools. Image Processing 2005 - [c15]Georgia D. Tourassi, Nevine H. Eltonsy, Adel Said Elmaghraby, Carey E. Floyd Jr.:
Detection of architectural distortion in mammograms using fractal analysis. Image Processing 2005 - [c14]Georgia D. Tourassi, Nevine H. Eltonsy, Adel Said Elmaghraby, Carey E. Floyd Jr.:
Automated detection of mammographic masses: preliminary assessment of an information-theoretic CAD scheme for reduction of false positives. Image Processing 2005 - 2004
- [c13]H. Erin Rickard, Georgia D. Tourassi, Adel Said Elmaghraby:
Unsupervised tissue segmentation in screening mammograms for automated breast density assessment. Image Processing 2004 - [c12]Georgia D. Tourassi, Carey E. Floyd Jr.:
Performance evaluation of an information-theoretic CAD scheme for the detection of mammographic architectural distortion. Image Processing 2004 - [c11]