Daniel C. Elton

According to our database, Daniel C. Elton authored at least 20 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Universal detection and segmentation of lymph nodes in multi-parametric MRI.

Tejas Sudharshan Mathai, Sungwon Lee, Thomas C. Shen, Daniel C. Elton, Zhiyong Lu, Ronald M. Summers

Int. J. Comput. Assist. Radiol. Surg., January, 2024

2022

Global-Local attention network with multi-task uncertainty loss for abnormal lymph node detection in MR images.

Shuai Wang, Yingying Zhu, Sungwon Lee, Daniel C. Elton, Thomas C. Shen, Youbao Tang, Yifan Peng, Zhiyong Lu, Ronald M. Summers

Medical Image Anal., 2022

Lymph node detection in T2 MRI with transformers.

Tejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton, Thomas C. Shen, Yifan Peng, Zhiyong Lu, Ronald M. Summers

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

Cardiovascular disease and all-cause mortality risk prediction from abdominal CT using deep learning.

Daniel C. Elton, Andy Chen, Perry J. Pickhardt, Ronald M. Summers

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021

Induction, Popper, and machine learning.

Bruce Nielson, Daniel C. Elton

CoRR, 2021

Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience - An initial exploration.

Daniel C. Elton

Cogn. Syst. Res., 2021

Learning Structure from Visual Semantic Features and Radiology Ontology for Lymph Node Classification on MRI.

Yingying Zhu, Shuai Wang, Qingyu Chen, Sungwon Lee, Thomas C. Shen, Daniel C. Elton, Zhiyong Lu, Ronald M. Summers

Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Detection of Lymph Nodes in T2 MRI Using Neural Network Ensembles.

Tejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton, Thomas C. Shen, Yifan Peng, Zhiyong Lu, Ronald M. Summers

Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

Common Pitfalls When Explaining AI and Why Mechanistic Explanation Is a Hard Problem.

Daniel C. Elton

Proceedings of Sixth International Congress on Information and Communication Technology, 2021

2020

Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Detection.

Yingying Zhu, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers

CoRR, 2020

Self-explainability as an alternative to interpretability for judging the trustworthiness of artificial intelligences.

Daniel C. Elton

CoRR, 2020

Cross-domain Medical Image Translation by Shared Latent Gaussian Mixture Model.

Yingying Zhu, Youbao Tang, Yuxing Tang, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Deep Small Bowel Segmentation with Cylindrical Topological Constraints.

Seung Yeon Shin, Sungwon Lee, Daniel C. Elton, James L. Gulley, Ronald M. Summers

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Accurately identifying vertebral levels in large datasets.

Daniel C. Elton, Veit Sandfort, Perry J. Pickhardt, Ronald M. Summers

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Independent Vector Analysis for Molecular Data Fusion: Application to Property Prediction and Knowledge Discovery of Energetic Materials.

Zois Boukouvalas, Monica Puerto, Daniel C. Elton, Peter W. Chung, Mark D. Fuge

Proceedings of the 28th European Signal Processing Conference, 2020

Self-explaining AI as an Alternative to Interpretable AI.

Daniel C. Elton

Proceedings of the Artificial General Intelligence - 13th International Conference, 2020

Automatic recognition of abdominal lymph nodes from clinical text.

Yifan Peng, Sungwon Lee, Daniel C. Elton, Thomas C. Shen, Yuxing Tang, Qingyu Chen, Shuai Wang, Yingying Zhu, Ronald M. Summers, Zhiyong Lu

Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020

2019

Deep learning for molecular generation and optimization - a review of the state of the art.

Daniel C. Elton, Zois Boukouvalas, Mark D. Fuge, Peter W. Chung

CoRR, 2019

Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora.

Daniel C. Elton, Dhruv Turakhia, Nischal Reddy, Zois Boukouvalas, Mark D. Fuge, Ruth M. Doherty, Peter W. Chung

CoRR, 2019

2018

Independent Vector Analysis for Data Fusion Prior to Molecular Property Prediction with Machine Learning.

Zois Boukouvalas, Daniel C. Elton, Peter W. Chung, Mark D. Fuge

CoRR, 2018