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Georgia D. Tourassi
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2020 – today
- 2024
- [j33]Alina Peluso
, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd-Yusof
Deep learning uncertainty quantification for clinical text classification. J. Biomed. Informatics 149: 104576 (2024) - [j32]Hong-Jun Yoon
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
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
Adiabatic Quantum Support Vector Machines. CoRR abs/2401.12485 (2024) - 2023
- [j31]Sergio Cerutti
Guest Editorial Advancing Biomedical Discovery and Healthcare Delivery Through Digital Technology. IEEE J. Biomed. Health Informatics 27(6): 2656-2659 (2023) - [j30]Junqi Yin
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
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
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
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
Deep active learning for classifying cancer pathology reports. BMC Bioinform. 22(1): 113 (2021) - [j26]Mohammed M. Alawad
Privacy-Preserving Deep Learning NLP Models for Cancer Registries. IEEE Trans. Emerg. Top. Comput. 9(3): 1219-1230 (2021) - [j25]Shang Gao
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
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
Knowledge Graph-Enabled Cancer Data Analytics. IEEE J. Biomed. Health Informatics 24(7): 1952-1967 (2020) - [c74]Hong-Jun Yoon
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
Classifying cancer pathology reports with hierarchical self-attention networks. Artif. Intell. Medicine 101 (2019) - [j20]Shuayb Zarar, Georgia D. Tourassi
Guest Editorial: AI Enabled Connected Health Informatics. IEEE J. Biomed. Health Informatics 23(3): 921-922 (2019) - [c73]Abhishek Kumar Dubey, Jacob D. Hinkle
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
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
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
Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. IEEE BigData 2019: 4561-4564 - [c66]Mohammed M. Alawad
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
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. Medical Imaging: 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
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
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
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
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
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
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
Shapelet analysis of pupil dilation for modeling visuo-cognitive behavior in screening mammography. Medical Imaging: 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
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
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
Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening. Medical Imaging: 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. Medical Imaging: Computer-Aided Diagnosis 2012: 83151Y - 2011
- [j10]Maciej A. Mazurowski, Joseph Y. Lo
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
Perception-driven IT-CADe analysis for the detection of masses in screening mammography: initial investigation. Medical Imaging: 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. Medical Imaging: Computer-Aided Diagnosis 2009: 72600F - [c39]Georgia D. Tourassi
Information-theoretic CAD system in mammography: improved mass detection by incorporating a Gaussian saliency map. Medical Imaging: 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. Medical Imaging: Computer-Aided Diagnosis 2009: 726018 - 2008
- [j9]Maciej A. Mazurowski, Piotr A. Habas, Jacek M. Zurada, Joseph Y. Lo
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
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
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. Medical Imaging: Computer-Aided Diagnosis 2008: 69151K - [c32]Swatee Singh, Georgia D. Tourassi
Computer-aided detection of breast masses in tomosynthesis reconstructed volumes using information-theoretic similarity measures. Medical Imaging: 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. Medical Imaging: Computer-Aided Diagnosis 2008: 691527 - 2007
- [j8]Nevine H. Eltonsy, Georgia D. Tourassi
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
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
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
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
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
Particle swarm optimization of neural network CAD systems with clinically relevant objectives. Medical Imaging: Computer-Aided Diagnosis 2007: 65140M - [c25]Georgia D. Tourassi
Cross-digitizer robustness of a knowledge-based CAD system for mass detection in mammograms. Medical Imaging: Computer-Aided Diagnosis 2007: 65141Y - [c24]Georgia D. Tourassi
Incorporation of a multiscale texture-based approach to mutual information matching for improved knowledge-based detection of masses in screening mammograms. Medical Imaging: Computer-Aided Diagnosis 2007: 651403 - [c23]Nevine H. Eltonsy, Georgia D. Tourassi
Contribution of Haar wavelets and MPEG-7 textural features for false positive reduction in a CAD system for the detection of masses in mammograms. Medical Imaging: Computer-Aided Diagnosis 2007: 651404 - [c22]Swatee Singh, Georgia D. Tourassi
Breast mass detection in tomosynthesis projection images using information-theoretic similarity measures. Medical Imaging: Computer-Aided Diagnosis 2007: 651415 - 2006
- [j7]Mia K. Markey
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
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
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
Confidence-based stratification of CAD recommendations with application to breast cancer detection. Medical Imaging: Image Processing 2006: 61445G - 2005
- [j6]Mark P. Wachowiak, Renata Smolíkova, Georgia D. Tourassi
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
Estimation of generalized entropies with sample spacing. Pattern Anal. Appl. 8(3): 303-303 (2005) - [c18]Aleksey Fadeev, Nevine H. Eltonsy, Georgia D. Tourassi
Adapted morphing model for 3D volume reconstruction applied to abdominal CT images. Medical Imaging: Image-Guided Procedures 2005 - [c17]Nevine H. Eltonsy, Georgia D. Tourassi
DNA: directional neighborhood analysis for detection of breast masses in screening mammograms. Medical Imaging: Image Processing 2005 - [c16]Piotr A. Habas, Georgia D. Tourassi
A novel technique for assessing the case-specific reliability of decisions made by CAD tools. Medical Imaging: Image Processing 2005 - [c15]Georgia D. Tourassi
Detection of architectural distortion in mammograms using fractal analysis. Medical Imaging: Image Processing 2005 - [c14]Georgia D. Tourassi
Automated detection of mammographic masses: preliminary assessment of an information-theoretic CAD scheme for reduction of false positives. Medical Imaging: Image Processing 2005 - 2004
- [c13]H. Erin Rickard, Georgia D. Tourassi
Unsupervised tissue segmentation in screening mammograms for automated breast density assessment. Medical Imaging: Image Processing 2004 - [c12]Georgia D. Tourassi
Performance evaluation of an information-theoretic CAD scheme for the detection of mammographic architectural distortion. Medical Imaging: Image Processing 2004 - [c11]Georgia D. Tourassi
Computer-assisted diagnosis of mammographic masses using an information-theoretic image retrieval scheme with BIRADs-based relevance feedback. Medical Imaging: Image Processing 2004 - 2003
- [j4]Mia K. Markey
Self-organizing map for cluster analysis of a breast cancer database. Artif. Intell. Medicine 27(2): 113-127 (2003) - [c10]Georgia D. Tourassi
Validation of a constraint satisfaction neural network for breast cancer disgnosis: new results from 1030 cases. Medical Imaging: Image Processing 2003 - [c9]Georgia D. Tourassi
Content-based image retrieval as a computer aid for the detection of mammographic masses. Medical Imaging: Image Processing 2003 - [c8]Mark P. Wachowiak, Renata Smolíkova, Georgia D. Tourassi
Similarity metrics based on nonadditive entropies for 2D-3D multimodal biomedical image registration. Medical Imaging: Image Processing 2003 - 2002
- [j3]Mia K. Markey
Perceptron error surface analysis: a case study in breast cancer diagnosis. Comput. Biol. Medicine 32(2): 99-109 (2002) - [c7]Mia K. Markey
Cluster analysis of BI-RADS descriptions of biopsy-proven breast lesions. Medical Imaging: Image Processing 2002 - 2001
- [j2]Georgia D. Tourassi
Multifractal texture analysis of perfusion lung scans as a potential diagnostic tool for acute pulmonary embolism. Comput. Biol. Medicine 31(1): 15-25 (2001) - 2000
- [j1]Georgia D. Tourassi
Fractal Texture Analysis of Perfusion Lung Scans. Comput. Biomed. Res. 33(3): 161-171 (2000) - [c6]Georgia D. Tourassi
Use of a constraint satisfaction neural network for breast cancer diagnosis and dynamic scenarios simulation. Medical Imaging: Image Processing 2000
1990 – 1999
- 1999
- [c5]Georgia D. Tourassi, Carey E. Floyd Jr., Joseph Y. Lo:
A constraint satisfaction neural network for medical diagnosis. IJCNN 1999: 3632-3635 - [c4]Carey E. Floyd Jr., Joseph Y. Lo, Georgia D. Tourassi
Case-based reasoning as a computer aid to diagnosis. Medical Imaging: Image Processing 1999 - [c3]Erik D. Frederick, Georgia D. Tourassi
Java interface to a computer-aided diagnosis system for acute pulmonary embolism using PIOPED findings. Medical Imaging: Image Processing 1999 - 1997
- [c2]Georgia D. Tourassi, Nicholas P. Xenopoulos:
An artificial neural network to predict mortality in patients who undergo percutaneous coronary interventions. ICNN 1997: 2464-2467 - 1996
- [c1]Carey E. Floyd Jr., Georgia D. Tourassi
Use of genetic algorithms for computer-aided diagnosis of breast cancers from image features. Medical Imaging: Image Processing 1996
Coauthor Index
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