Publications by authors named "Georgia Tourassi"

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Redefining druggable targets with artificial intelligence.
Karen Akinsanya, Mohammed AlQuraishi, Ann Boija, John Chodera, Anna Cichońska, Georgia Tourassi

Nat Biotechnol· September 2025

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The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection.
Jeffrey Buchsbaum, Jacek Capala, Ceferino Obcemea, Cynthia Keppel, Makoto Asai, Georgia Tourassi

Med Phys· December 2024

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Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.
Linus Manubens-Gil, Zhi Zhou, Hanbo Chen, Arvind Ramanathan, Xiaoxiao Liu, Georgia Tourassi

Nat Methods· October 2024

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Development of message passing-based graph convolutional networks for classifying cancer pathology reports.
Hong-Jun Yoon, Hilda B Klasky, Andrew E Blanchard, J Blair Christian, Eric B Durbin, Georgia D Tourassi

BMC Med Inform Decis Mak· September 2024

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Machine learning and deep learning tools for the automated capture of cancer surveillance data.
Elizabeth Hsu, Heidi Hanson, Linda Coyle, Jennifer Stevens, Georgia Tourassi

J Natl Cancer Inst Monogr· August 2024

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Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.
Anurag Verma, Jennifer E Huffman, Alex Rodriguez, Mitchell Conery, Molei Liu, Georgia Tourassi

Science· July 2024

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Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program.
Alex Rodriguez, Youngdae Kim, Tarak Nath Nandi, Karl Keat, Rachit Kumar, Georgia Tourassi

bioRxiv· May 2024

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Deep learning uncertainty quantification for clinical text classification.
Alina Peluso, Ioana Danciu, Hong-Jun Yoon, Jamaludin Mohd Yusof, Tanmoy Bhattacharya, Georgia D Tourassi

J Biomed Inform· January 2024

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Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing.
Usman Mahmood, Amita Shukla-Dave, Heang-Ping Chan, Karen Drukker, Ravi K Samala, Georgia Tourassi

BJR Artif Intell· January 2024

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AI and machine learning in medical imaging: key points from development to translation.
Ravi K Samala, Karen Drukker, Amita Shukla-Dave, Heang-Ping Chan, Berkman Sahiner, Georgia Tourassi

BJR Artif Intell· January 2024

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.
Linus Manubens-Gil, Zhi Zhou, Hanbo Chen, Arvind Ramanathan, Xiaoxiao Liu, Georgia Tourassi

Nat Methods· June 2023

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Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program.
Anurag Verma, Jennifer E Huffman, Alex Rodriguez, Mitchell Conery, Molei Liu, Georgia Tourassi

medRxiv· June 2023

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The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances via Discovery in Physical Sciences.
Cynthia Keppel, Andrew Weisenberger, Tatjana Atanasijevic, Shumin Wang, George Zubal, Georgia Tourassi

Med Phys· March 2023

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AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.
Lubomir Hadjiiski, Kenny Cha, Heang-Ping Chan, Karen Drukker, Lia Morra, Georgia Tourassi

Med Phys· February 2023

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Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports.
Kevin De Angeli, Shang Gao, Andrew Blanchard, Eric B Durbin, Xiao-Cheng Wu, Georgia Tourassi

JAMIA Open· October 2022

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A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification.
Andrew E Blanchard, Shang Gao, Hong-Jun Yoon, J Blair Christian, Eric B Durbin, Georgia D Tourassi

IEEE J Biomed Health Inform· June 2022

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Predictive Radiation Oncology - A New NCI-DOE Scientific Space and Community.
Jeffrey C Buchsbaum, David A Jaffray, Demba Ba, Lynn L Borkon, Christine Chalk, Georgia Tourassi

Radiat Res· April 2022

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Optimal vocabulary selection approaches for privacy-preserving deep NLP model training for information extraction and cancer epidemiology.
Hong-Jun Yoon, Christopher Stanley, J Blair Christian, Hilda B Klasky, Andrew E Blanchard, Georgia D Tourassi

Cancer Biomark· March 2022

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Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types.
Kevin De Angeli, Shang Gao, Ioana Danciu, Eric B Durbin, Xiao-Cheng Wu, Georgia D Tourassi

J Biomed Inform· January 2022

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Artificial intelligence in cancer research, diagnosis and therapy.
Olivier Elemento, Christina Leslie, Johan Lundin, Georgia Tourassi

Nat Rev Cancer· December 2021

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Pharmacoepidemiology, Machine Learning, and COVID-19: An Intent-to-Treat Analysis of Hydroxychloroquine, With or Without Azithromycin, and COVID-19 Outcomes Among Hospitalized US Veterans.
Hanna Gerlovin, Daniel C Posner, Yuk-Lam Ho, Christopher T Rentsch, Janet P Tate, Georgia Tourassi

Am J Epidemiol· November 2021

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Limitations of Transformers on Clinical Text Classification.
Shang Gao, Mohammed Alawad, M Todd Young, John Gounley, Noah Schaefferkoetter, Georgia Tourassi

IEEE J Biomed Health Inform· September 2021

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COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients.
Mark Stewart, Carla Rodriguez-Watson, Adem Albayrak, Julius Asubonteng, Andrew Belli, Georgia Tourassi

PLoS One· March 2021

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Deep active learning for classifying cancer pathology reports.
Kevin De Angeli, Shang Gao, Mohammed Alawad, Hong-Jun Yoon, Noah Schaefferkoetter, Georgia Tourassi

BMC Bioinformatics· March 2021

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Privacy-Preserving Deep Learning NLP Models for Cancer Registries.
Mohammed Alawad, Hong-Jun Yoon, Shang Gao, Brent Mumphrey, Xiao-Cheng Wu, Georgia Tourassi

IEEE Trans Emerg Top Comput· April 2020

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