D. Raicu

发表

Evaluation Challenges for Computer-Aided Diagnostic Characterization: Shape Disagreements in the Lung Image Database Consortium Pulmonary Nodule Dataset

S. Armato, J. Furst, W. Horsthemke, 2011 .

A Hybrid Approach for Liver Segmentation

J. Furst, D. Raicu, Ruchaneewan Susomboon, 2007 .

Automatic Segmentation of Clinical Texts-Preliminary Results

Dina Demner-Fushman, J. Furst, D. Raicu, 2009 .

Local vs . Global Histogram-Based Color Image Clustering

Daniela Raicu, Bongani Malinga, D. Raicu, 2006 .

Pixel-Based Texture Classification of Tissues in Computed Tomography

J. Furst, D. Raicu, Ruchaneewan Susomboon, 2006 .

An Empirical Comparison of Machine Learning Algorithms for the Classification of Anthracis DNA Using Microarray Data

J. Furst, R. Settimi, D. Raicu, 2007 .

Association Rule Mining based Decision Tree Induction for Efficient Detection of Cancerous Masses in Mammogram

W. A. Atteya, D. Raicu, Ruchaneewan Susomboon, 2020 .

Characterizing the role of a high-volume cancer resection ecosystem on low-volume, high-quality surgical care.

R. Settimi, D. Raicu, P. Kuo, 2016, Surgery.

Roselyne B. Tchoua, J. Furst, D. Raicu, 2022, Medical Imaging.

Exploiting Variance in Radiologist-Defined Truth : Opportunities from the LIDC

Depaul, W. Horsthemke, D. Raicu, 2007 .

Natural Language Diagnostic tool for Radiologists

Depaul, A. Rasin, J. Furst, 2017 .

Ensemble Labeling Towards Scientific Information Extraction (ELSIE)

Jacob D. Furst, Alexander Rasin, Roselyne Tchoua, 2021, ICCS.

Developing Parameters for a Technology to Predict Patient Satisfaction in Naturalistic Clinical Encounters

Jacob D. Furst, Daniela Raicu, Enid Montague, 2020, HCI.

Building confidence and credibility into CAD with belief decision trees

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2017, Medical Imaging.

A Lookup and Reference Tool for Pulmonary Computed Tomography Nodules

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2007 .

An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files

Jacob D. Furst, Alexander Rasin, Priya Deshpande, 2017, MIH@KDD.

Classification of Tissues in Computed Tomography using Decision Trees

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2004 .

Visual Explanations from Deep Networks via Riemann-Stieltjes Integrated Gradient-based Localization

J. Furst, D. Raicu, Mirtha Lucas, 2022, ISVC.

Prediction of Chronic Fatigue Syndrome Using Decision Tree-Based Ensemble Methods

J. Furst, D. Raicu, Christine M. Bronikowski, 2011 .

Lung Nodule Malignancy Subtype Discovery with Semantic Learning

J. Furst, T. Ramaraj, D. Raicu, 2022, 2022 26th International Conference on Pattern Recognition (ICPR).

Contextualizing Lung Nodule Malignancy Predictions with Easy vs. Hard Image Classification

Roselyne B. Tchoua, J. Furst, T. Ramaraj, 2022, 2022 Fourth International Conference on Transdisciplinary AI (TransAI).

CompNet: A Designated Model to Handle Combinations of Images and Designed features

Roselyne B. Tchoua, J. Furst, D. Raicu, 2022, ArXiv.

Detecting and Characterizing Trends in Online Mental Health Discussions

Jonathan Gemmell, Daniela Raicu, Dante Chakravorti, 2018, 2018 IEEE International Conference on Data Mining Workshops (ICDMW).

Automatic extraction of informal topics from online suicidal ideation

Daniela Stan Raicu, Jonathan Gemmell, Samah J. Fodeh, 2018, BMC Bioinformatics.

Discovery of Informal Topics from Post Traumatic Stress Disorder Forums

Jonathan Gemmell, Daniela Raicu, Reilly Grant, 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets

Martin Styner, Jacob D. Furst, Thomas Lange, 2009, IEEE Transactions on Medical Imaging.

Oligonucleotide Microarray Identification of Bacillus Anthracis Strains Using Support Vector Machines

Jacob D. Furst, Daniela Stan Raicu, Michael V. Doran, 2007 .

Robust Heatmap Template Generation for COVID-19 Biomarker Detection

Miguel A. Lerma, J. Furst, D. Raicu, 2021 .

Mining Knowledge in Computer Tomography Image Databases

Daniela Stan Raicu, D. Raicu, 2007 .

Text Summarization towards Scientific Information Extraction

Peter M. Hastings, Roselyne B. Tchoua, J. Furst, 2022, 2022 IEEE 18th International Conference on e-Science (e-Science).

Ensemble Labeling towards Scientific Information Extraction (ELSIE)—Blob Extraction

Roselyne B. Tchoua, A. Rasin, J. Furst, 2021, eScience.

RUN-LENGTH ENCODING FOR VOLUMETRIC TEXTURE

Jacob D. Furst, Daniela Stan Raicu, Dong-Hui Xu, 2004 .

Presynaptic BK channel localization is dependent on the hierarchical organization of alpha-catulin and dystrobrevin and fine-tuned by CaV2 calcium channels

Mark J Alkema, J. Furst, D. Raicu, 2015, BMC Neuroscience.

Probabilistic lung nodule classification with belief decision trees

Jacob D. Furst, Dmitry Zinovev, Daniela Raicu, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Drusen segmentation with sparse volumetric SD-OCT sampling

Jacob Furst, Daniela Raicu, Amani Fawzi, 2021, Medical Imaging.

Robust Physician Gaze Prediction Using a Deep Learning Approach

Jacob Furst, Daniela Raicu, Enid Montague, 2020, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE).

Predicting Radiological Panel Opinions Using a Panel of Machine Learning Classifiers

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2009, Algorithms.

Machine-Sourced Segmentations vs. Expert-Sourced Segmentations for the Classification of Lung Nodules with Outlier Removal

Jacob D. Furst, Daniela Stan Raicu, Mayra Alejandra Molina Puentes, 2014, 2014 13th International Conference on Machine Learning and Applications.

Weak Segmentations and Ensemble Learning to Predict Semantic Ratings of Lung Nodules

Jacob D. Furst, Daniela Stan Raicu, Patrick Stein, 2013, 2013 12th International Conference on Machine Learning and Applications.

Mapping LIDC, RadLex™, and Lung Nodule Image Features

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2011, Journal of Digital Imaging.

Predicting LIDC diagnostic characteristics by combining spatial and diagnostic opinions

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2010, Medical Imaging.

Characterizing pulmonary nodule shape using a boundary-region approach

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2009, Medical Imaging.

Evaluation Challenges for Bridging Semantic Gap: Shape Disagreements on Pulmonary Nodules in the Lung Image Database Consortium

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2009, Int. J. Heal. Inf. Syst. Informatics.

Combining Boundaries and Ratings from Multiple Observers for Predicting Lung Nodule Characteristics

Jacob D. Furst, Daniela Stan Raicu, Ekarin Varutbangkul, 2008, 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies.

Bridging the Evaluation Gap Challenge to Diagnostic Labeling of Pulmonary Nodules

Jacob D. Furst, William H. Horsthemke, Daniela S. Raicu, 2008 .

Big Data Integration Case Study for Radiology Data Sources

Samuel G. Armato, Alexander Rasin, Priya Deshpande, 2018, 2018 IEEE Life Sciences Conference (LSC).

Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection

Jacob D. Furst, Daniela Stan Raicu, Natalia M. Jenuwine, 2018, Medical Imaging.

A shape-dependent variability metric for evaluating panel segmentations with a case study on LIDC

Jacob D. Furst, Samuel G. Armato, Daniela Raicu, 2010, Medical Imaging.

Mining association rules between low-level image features and high-level concepts

Ishwar K. Sethi, Daniela Stan Raicu, Ioana L. Coman, 2001, SPIE Defense + Commercial Sensing.

Applying Association Rule Mining to Semantic Data in the Lung Image Database Consortium

Jacob D. Furst, Brendan Kennedy, Miguel Carrazza, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Directional Invariance of Co-occurrence Matrices within the Liver

Jacob D. Furst, Daniela Stan Raicu, Daniel Li, 2008, 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies.

C. elegans search behavior analysis using Multivariate Dynamic Time Warping

Jacob D. Furst, Li Huang, Hongkyun Kim, 2016, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Automatic segmentation of clinical texts

Dina Demner-Fushman, David S. Channin, Jacob Furst, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Top issues in providing successful undergraduate research experiences

Jacob D. Furst, Daniela Stan Raicu, Hans-Peter Bischof, 2011, SIGCSE.

Enhancing undergraduate education: a REU model for interdisciplinary research

Jacob D. Furst, Daniela Stan Raicu, J. Furst, 2009, SIGCSE '09.

REUs: undergraduate research experiences and funding

Ingrid Russell, Joan Peckham, Fatma Mili, 2008 .

Drusen diagnosis comparison between hyper-spectral and color retinal images.

Jacob Furst, Yiyang Wang, Brian Soetikno, 2019, Biomedical optics express.

Commercial quality “awards” are not a strong indicator of quality surgical care

D. Raicu, P. Kuo, A. Kothari, 2018, Surgery.

Content-based image retrieval for pulmonary computed tomography nodule images

Jacob D. Furst, Daniela Stan Raicu, Tim Disney, 2007, SPIE Medical Imaging.

Augmenting LIDC dataset using 3D generative adversarial networks to improve lung nodule detection

Jacob D. Furst, Stephen Clark, Chufan Gao, 2019, Medical Imaging.

Multimodal Ranked Search over Integrated Repository of Radiology Data Sources

Jacob D. Furst, Alexander Rasin, Daniela Stan Raicu, 2019, KDIR.

Curriculum gDRO: Improving Lung Malignancy Classification through Robust Curriculum Task Learning

Roselyne B. Tchoua, J. Furst, T. Ramaraj, 2023, 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS).

eID: a system for exploration of image databases

Ishwar K. Sethi, Daniela Stan Raicu, I. Sethi, 2003, Inf. Process. Manag..

Federated learning in gaze recognition (FLIGR)

J. Furst, D. Raicu, 2021 .

Explainable Deep Learning for Biomarker Classification of OCT Images

Yiyang Wang, Jacob Furst, Amani A. Fawzi, 2020, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE).

No nodule left behind: evaluating lung nodule malignancy classification with different stratification schemes

Roselyne B. Tchoua, Thomas Zeng, J. Furst, 2023, Medical Imaging.

Content-based versus semantic-based retrieval: an LIDC case study

Jacob D. Furst, Daniela Stan Raicu, Sarah A. Jabon, 2009, Medical Imaging.

Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers

Jacob D. Furst, Daniela Stan Raicu, Michael Harris, 2013, MLDM.

Consensus Versus Disagreement in Imaging Research: a Case Study Using the LIDC Database

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2012, Journal of Digital Imaging.

Building an Ensemble of Probabilistic Classifiers for Lung Nodule Interpretation

Jacob D. Furst, Daniela Stan Raicu, Dmitry Zinovev, 2011, 2011 10th International Conference on Machine Learning and Applications and Workshops.

A classification approach for anatomical regions segmentation

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2005, IEEE International Conference on Image Processing 2005.

Interactive deep learning for explainable retinal disease classification

Roselyne B. Tchoua, J. Furst, D. Raicu, 2022, Medical Imaging.

Building an ensemble system for diagnosing masses in mammograms

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2012, International Journal of Computer Assisted Radiology and Surgery.

Computational Methods for Tracking, Quantitative Assessment, and Visualization of C. elegans Locomotory Behavior

Jacob Furst, Daniela Raicu, Valerie Simonis, 2015, PloS one.

Comparing automatically extracted topics from online suicidal ideation and the responses they invoke

Daniela Raicu, Elise Glaser, Alexander Morain, 2020, SAC.

CO-OCCURRENCE MATRICES FOR VOLUMETRIC DATA

Jacob D. Furst, Daniela Stan Raicu, Dong-Hui Xu, 2004 .

Using BI-RADS Descriptors and Ensemble Learning for Classifying Masses in Mammograms

Yu Zhang, Jacob D. Furst, Noriko Tomuro, 2009, MCBR-CDS.

Predictive Data Mining for Lung Nodule Interpretation

Jacob D. Furst, Daniela Stan Raicu, William H. Horsthemke, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Using Machine Learning Algorithms to Detect Suicide Risk Factors on Twitter

Jonathan Gemmell, Samah Fodeh, Taihua Li, 2019, 2019 International Conference on Data Mining Workshops (ICDMW).

Digital Commons@DePaul Digital Commons@DePaul

Roselyne B. Tchoua, A. Rasin, J. Furst, 2023 .

Measurement of similarity in C. elegans healthspan using dynamic time warping on movement features

Jacob D. Furst, Yiyang Wang, Hongkyun Kim, 2020 .

Evaluation of Eye Gaze Dynamics During Physician-Patient-Computer Interaction in Federally Qualified Health Centers: Systematic Analysis.

J. Furst, E. Montague, D. Raicu, 2023, JMIR Human Factors.

Approaches to Evaluating Eye Gaze Patterns between Physician-Patient Interaction in Primary Care Clinic

Jacob D. Furst, Enid Montague, Daniela Raicu, 2021, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Bioinformatics Original Paper Oligonucleotide Microarray Identification of Bacillus Anthracis Strains Using Support Vector Machines

D. Raicu, M. Doran, J. D. Furst, 2022 .

Assessment of Medical Reports Uncertainty through Topic Modeling and Machine Learning

Jacob D. Furst, Daniela Stan Raicu, Mengyuan Shang, 2020, 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS).

DiiS: A Biomedical Data Access Framework for Aiding Data Driven Research Supporting FAIR Principles

Jacob D. Furst, Sameer Antani, Alexander Rasin, 2019, Data.

Predicting physician gaze in clinical settings using optical flow and positioning

Jacob Furst, Daniela Raicu, Enid Montague, 2020, 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ).

Investigation on Feature Selection to Improve Classification of Abdominal Organs in CT Images

Yu Zhang, Noriko Tomuro, Daniela Stan Raicu, 2006 .

Ontology-Based Radiology Teaching File Summarization, Coverage, and Integration

Eli T. Brown, Priya Deshpande, Alexander Rasin, 2020, Journal of Digital Imaging.

Contrast enhancement of soft tissues in computed tomography images

Jacob D. Furst, Daniela Stan Raicu, Roman Lerman, 2006, SPIE Medical Imaging.

Semantics and image content integration for pulmonary nodule interpretation in thoracic computed tomography

S. Armato, D. Raicu, D. Channin, 2007, SPIE Medical Imaging.

BRISC—An Open Source Pulmonary Nodule Image Retrieval Framework

David S. Channin, Jacob Furst, Tim Disney, 2007, Journal of Digital Imaging.

Detecting age-related macular degeneration (AMD) biomarker images using MFCC and texture features

Jacob D. Furst, Yiyang Wang, Daniela Raicu, 2020, Medical Imaging.

Automatic segmentation of clinical texts

Dina Demner-Fushman, J. Furst, D. Raicu, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Enhancing sensitivity in lung nodule malignancy classification: incorporating cost values into deep learning-based CAD systems

D. Raicu, Yiyang Wang, Jacob D. Furst, 2024, Medical Imaging.

Leveraging Interpretable Features and Clustering Agreements for Assistive Materials Discovery

D. Raicu, Jacob D. Furst, Roselyne Tchoua, 2023, 2023 Fifth International Conference on Transdisciplinary AI (TransAI).

A Texture Dictionary for Human Organs Tissues’ Classification

Jacob D. Furst, Daniela Stan Raicu, David S. Channin, 2004 .

A Run-Length Encoding Approach for Path Analysis of C. elegans Search Behavior

Jacob D. Furst, Huang Li, Hongkyun Kim, 2016, Comput. Math. Methods Medicine.