Lynne Penberthy

Orcid: 0000-0001-9372-9869

According to our database1, Lynne Penberthy authored at least 15 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Development of message passing-based graph convolutional networks for classifying cancer pathology reports.
BMC Medical Informatics Decis. Mak., December, 2024

Deep learning uncertainty quantification for clinical text classification.
J. Biomed. Informatics, January, 2024

Topological Interpretability for Deep Learning.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2024

2022
A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification.
IEEE J. Biomed. Health Informatics, 2022

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types.
J. Biomed. Informatics, 2022

2021
Privacy-Preserving Deep Learning NLP Models for Cancer Registries.
IEEE Trans. Emerg. Top. Comput., 2021

Integration of Domain Knowledge using Medical Knowledge Graph Deep Learning for Cancer Phenotyping.
CoRR, 2021

Deep active learning for classifying cancer pathology reports.
BMC Bioinform., 2021

2020
Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports.
J. Biomed. Informatics, 2020

Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks.
J. Am. Medical Informatics Assoc., 2020

Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports.
CoRR, 2020

Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles.
Proceedings of the Heterogeneous Data Management, Polystores, and Analytics for Healthcare, 2020

2019
Classifying cancer pathology reports with hierarchical self-attention networks.
Artif. Intell. Medicine, 2019

Adversarial Training for Privacy-Preserving Deep Learning Model Distribution.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2017
Leveraging Large-Scale Computing for Population Information Integration, Analysis, and Modeling.
Proceedings of the AMIA 2017, 2017


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