Analysis of tumor as an inverse problem provides a novel theoretical framework for understanding tumor biology and therapy. - Robert A. Gatenby; Philip K. Maini; Edward T. Gawlinski (Appl. Math. Lett., 2002)

Modeling Cancer as an Evolutionary Game. - Thomas L. Vincent; Robert A. Gatenby (IGTR, 2005)

Somatic Evolution of Cancer. - Thomas L. Vincent; Robert A. Gatenby (IGTR, 2008)

Assessing Radiology Resident Preparedness to Manage IV Contrast Media Reactions Using Simulation Technology. - Elizabeth A. Krupinski; Bhavika Patel; William Berger; Allan J. Hamilton; Alyson E. Knapp; Gary J. Becker; Robert A. Gatenby (MMVR, 2009)

Developing a classifier model for lung tumors in CT-scan images. - Satrajit Basu; Lawrence O. Hall; Dmitry B. Goldgof; Yuhua Gu; Virendra Kumar; Jung Choi; Robert J. Gillies; Robert A. Gatenby (SMC, 2011)

Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2013)

A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies (SMC, 2013)

Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. - Yuhua Gu; Virendra Kumar; Lawrence O. Hall; Dmitry B. Goldgof; Ching-Yen Li; René Korn; Claus Bendtsen; Emmanuel Rios Velazquez; Andre Dekker; Hugo J. W. L. Aerts; Philippe Lambin; Xiuli Li; et al. (Pattern Recognit., 2013)

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. - Baishali Chaudhury; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2014)

Prediction of treatment response and metastatic disease in soft tissue sarcoma. - Hamidreza Farhidzadeh; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Meera Raghavan; Robert A. Gatenby (Computer-Aided Diagnosis, 2014)

Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. - Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (SMC, 2014)

Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. - Samuel H. Hawkins; John N. Korecki; Yoganand Balagurunathan; Yuhua Gu; Virendra Kumar; Satrajit Basu; Lawrence O. Hall; Dmitry B. Goldgof; Robert A. Gatenby; Robert J. Gillies (IEEE Access, 2014)

Test-Retest Reproducibility Analysis of Lung CT Image Features. - Yoganand Balagurunathan; Virendra Kumar; Yuhua Gu; Jongphil Kim; Hua Wang; Ying Liu; Dmitry B. Goldgof; Lawrence O. Hall; René Korn; Binsheng Zhao; Lawrence H. Schwartz; Satrajit Basu; et al. (J. Digit. Imaging, 2014)

Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. - Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2015)

Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. - Hamidreza Farhidzadeh; Baishali Chaudhury; Mu Zhou; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (Computer-Aided Diagnosis, 2015)

Imbalanced learning for clinical survival group prediction of brain tumor patients. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2015)

Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. - Mu Zhou; Lawrence O. Hall; Dmitry B. Goldgof; Robin Russo; Robert J. Gillies; Robert A. Gatenby (Computer-Aided Diagnosis, 2015)

Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. - Baishali Chaudhury; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Jennifer S. Drukteinis (SMC, 2015)

Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. - Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (SMC, 2015)

Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance. - Daniel Nichol; Peter Jeavons 001; Alexander G. Fletcher; Robert A. Bonomo; Philip K. Maini; Jerome L. Paul; Robert A. Gatenby; Alexander R. A. Anderson; Jacob G. Scott (PLoS Comput. Biol., 2015)

Exploring deep features from brain tumor magnetic resonance images via transfer learning. - Renhao Liu; Lawrence O. Hall; Dmitry B. Goldgof; Mu Zhou; Robert A. Gatenby; Kaoutar Ben Ahmed (IJCNN, 2016)

Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. - Baishali Chaudhury; Mu Zhou; Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Robert J. Weinfurtner; Jennifer S. Drukteinis (Computer-Aided Diagnosis, 2016)

Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. - Hamidreza Farhidzadeh; Baishali Chaudhury; Jacob G. Scott; Dmitry B. Goldgof; Lawrence O. Hall; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (Computer-Aided Diagnosis, 2016)

Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. - Benjamin Geiger; Samuel H. Hawkins; Lawrence O. Hall; Dmitry B. Goldgof; Yoganand Balagurunathan; Robert A. Gatenby; Robert J. Gillies (Computer-Aided Diagnosis, 2016)

A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. - Hamidreza Farhidzadeh; Dmitry B. Goldgof; Lawrence O. Hall; Jacob G. Scott; Robert A. Gatenby; Robert J. Gillies; Meera Raghavan (SMC, 2016)

Fine-tuning convolutional deep features for MRI based brain tumor classification. - Kaoutar Ben Ahmed; Lawrence O. Hall; Dmitry B. Goldgof; Renhao Liu; Robert A. Gatenby (Computer-Aided Diagnosis, 2017)

Synthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction. - Renhao Liu; Lawrence O. Hall; Kevin W. Bowyer; Dmitry B. Goldgof; Robert A. Gatenby; Kaoutar Ben Ahmed (SMC, 2017)

Aggregation Effects and Population-Based Dynamics as a Source of Therapy Resistance in Cancer. - Joel S. Brown; Jessica J. Cunningham; Robert A. Gatenby (IEEE Trans. Biomed. Eng., 2017)

Stem Cell Plasticity and Niche Dynamics in Cancer Progression. - Noemi Picco; Robert A. Gatenby; Alexander R. A. Anderson (IEEE Trans. Biomed. Eng., 2017)

Neuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data. - Kaoutar Ben Ahmed; Lawrence O. Hall; Renhao Liu; Robert A. Gatenby; Dmitry B. Goldgof (SMC, 2019)

Cytoplasmic convection currents and intracellular temperature gradients. - Rachel Howard; Aaron Scheiner; Jessica J. Cunningham; Robert A. Gatenby (PLoS Comput. Biol., 2019)

CancerCellTracker: a brightfield time-lapse microscopy framework for cancer drug sensitivity estimation. - Qibing Jiang; Praneeth Sudalagunta; Maria C. Silva; Rafael R. Canevarolo; Xiaohong Zhao; Khandakar Tanvir Ahmed; Raghunandan Reddy Alugubelli; Gabriel Deavila; Alexandre Tungesvik; Lia Perez; Robert A. Gatenby; Robert J. Gillies; et al. (Bioinform., 2022)

Mistic: An open-source multiplexed image t-SNE viewer. - Sandhya Prabhakaran; Chandler Gatenbee; Mark Robertson-Tessi; Jeffrey West; Amer A. Beg; Jhanelle Gray; Scott Antonia; Robert A. Gatenby; Alexander R. A. Anderson (Patterns, 2022)

Modeling non-genetic information dynamics in cells using reservoir computing. - Dipesh Niraula; Issam El-Naqa; Jack Adam Tuszynski; Robert A. Gatenby (CoRR, 2023)

Deep reinforcement learning identifies personalized intermittent androgen deprivation therapy for prostate cancer. - Yitao Lu; Qian Chu; Zhen Li 013; Mengdi Wang; Robert A. Gatenby; Qingpeng Zhang (Briefings Bioinform., 2024)