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ORCIDKyle J. Lafata
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2020 – today
- 2025
[j3]Yuqi Wang
, Aarzu Gupta, Fakrul Islam Tushar, Breylon Riley, Avivah Wang, Tina D. Tailor, Stacy L. Tantum, Jian-Guo Liu, Mustafa R. Bashir, Joseph Y. Lo, Kyle J. Lafata:
Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT. Artif. Intell. Medicine 160: 103055 (2025)- [j2]Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe, Amareswararao Kavuri, Lavsen Dahal, Brian P. Harrawood, Milo Fryling, Mojtaba Zarei, Saman Sotoudeh-Paima, Fong Chi Ho, Dhrubajyoti Ghosh, Michael R. Harowicz, Tina D. Tailor, Sheng Luo, William Paul Segars, Ehsan Abadi, Kyle J. Lafata, Joseph Y. Lo, Ehsan Samei:
Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection. Medical Image Anal. 103: 103576 (2025) - [j1]Lavsen Dahal, Mobina Ghojogh Nejad, Liesbeth Vancoillie, Dhrubajyoti Ghosh, Yubraj Bhandari, David Kim, Fong Chi Ho, Fakrul Islam Tushar, Sheng Luo, Kyle J. Lafata, Ehsan Abadi, Ehsan Samei, Joseph Y. Lo, William Paul Segars:
XCAT 3.0: A comprehensive library of personalized digital twins derived from CT scans. Medical Image Anal. 103: 103636 (2025) - [c6]Kaouther Mouheb, Mobina Ghojogh Nejad, Lavsen Dahal, Ehsan Samei, Kyle J. Lafata, William Paul Segars, Joseph Y. Lo:
Large Intestine 3D Shape Refinement Using Conditional Latent Point Diffusion Models. ShapeMI@MICCAI 2025: 103-116 - [i10]Fakrul Islam Tushar, Lavsen Dahal, Cindy McCabe, Fong Chi Ho, Paul Segars, Ehsan Abadi, Kyle J. Lafata, Ehsan Samei, Joseph Y. Lo:
SYN-LUNGS: Towards Simulating Lung Nodules with Anatomy-Informed Digital Twins for AI Training. CoRR abs/2502.21187 (2025) - [i9]Michael E. Garcia-Alcoser, Mobina Ghojogh Nejad, Fakrul Islam Tushar, David Kim, Kyle J. Lafata, Geoffrey D. Rubin, Joseph Y. Lo:
Evaluating Large Language Models for Zero-Shot Disease Labeling in CT Radiology Reports Across Organ Systems. CoRR abs/2506.03259 (2025) - 2024
- [c5]Anthony Liardo, Aritra Ray, Farshad Firouzi, Kyle Lafata, Krishnendu Chakrabarty:
Neural Architecture Search for Blood Glucose Prediction in Type-1 Diabetics. BSN 2024: 1-4 - [c4]Aritra Ray, Farshad Firouzi, Kyle Lafata, Krishnendu Chakrabarty:
Preserving Accuracy While Stealing Watermarked Deep Neural Networks. ICMLA 2024: 1466-1473 - [i8]Fakrul Islam Tushar, Avivah Wang, Lavsen Dahal, Michael R. Harowicz, Kyle J. Lafata, Tina D. Tailor, Joseph Y. Lo:
AI in Lung Health: Benchmarking Detection and Diagnostic Models Across Multiple CT Scan Datasets. CoRR abs/2405.04605 (2024) - [i7]Lavsen Dahal, Mobina Ghojogh Nejad, Dhrubajyoti Ghosh, Yubraj Bhandari, David Kim, Fong Chi Ho, Fakrul Islam Tushar, Sheng Luo, Kyle J. Lafata, Ehsan Abadi, Ehsan Samei, Joseph Y. Lo, William Paul Segars:
XCAT-3.0: A Comprehensive Library of Personalized Digital Twins Derived from CT Scans. CoRR abs/2405.11133 (2024) - 2023
- [c3]Aritra Ray, Kyle Lafata, Zhaobo Zhang, Ying Xiong, Krishnendu Chakrabarty:
Privacy-preserving Job Scheduler for GPU Sharing. CCGridW 2023: 337-339 - [c2]Peter Domanski, Aritra Ray, Farshad Firouzi, Kyle Lafata, Krishnendu Chakrabarty, Dirk Pflüger:
Blood Glucose Prediction for Type-1 Diabetics using Deep Reinforcement Learning. ICDH 2023: 339-347 - [i6]Lucas Kreiss, Shaowei Jiang, Xiang Li, Shiqi Xu, Kevin C. Zhou, Alexander Mühlberg, Kyung Chul Lee, Kanghyun Kim, Amey Chaware, D. Michael Ando, Laura Barisoni, Seung Ah Lee, Guoan Zheng, Kyle Lafata, Oliver Friedrich, Roarke Horstmeyer:
Digital staining in optical microscopy using deep learning - a review. CoRR abs/2303.08140 (2023) - [i5]Yuqi Wang, Jacob A. Macdonald, Katelyn R. Morgan, Danielle Hom, Sarah Cubberley, Kassi Sollace, Nicole Casasanto, Islam H. Zaki, Kyle J. Lafata, Mustafa R. Bashir:
Duke Spleen Data Set: A Publicly Available Spleen MRI and CT dataset for Training Segmentation. CoRR abs/2305.05732 (2023) - [i4]Yuqi Wang, Aarzu Gupta, David Carpenter, Trey Mullikin, Zachary J. Reitman, Scott Floyd, John Kirkpatrick, Joseph K. Salama, Paul W. Sperduto, Jian-Guo Liu, Mustafa R. Bashir, Kyle J. Lafata:
A personalized Uncertainty Quantification framework for patient survival models: estimating individual uncertainty of patients with metastatic brain tumors in the absence of ground truth. CoRR abs/2311.17173 (2023) - 2022
- [c1]Alex J. Allphin, Yvonne M. Mowery, Kyle J. Lafata, Darin P. Clark, A. Basil, Rico Castillo, Matthew D. Holbrook, Ketan B. Ghaghada, Cristian T. Badea:
Spectral micro-CT and radiomic analysis for classification of tumors based on lymphocytic burden in cancer therapy studies. Biomedical Applications in Molecular, Structural, and Functional Imaging 2022 - [i3]Zhenyu Yang, Zongsheng Hu, Hangjie Ji, Kyle J. Lafata, Scott Floyd, Fang-Fang Yin, Chunhao Wang:
A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation. CoRR abs/2203.00628 (2022) - [i2]Zhenyu Yang, Kyle J. Lafata, Eugene Vaios, Zongsheng Hu, Trey Mullikin, Fang-Fang Yin, Chunhao Wang:
Quantifying U-Net Uncertainty in Multi-Parametric MRI-based Glioma Segmentation by Spherical Image Projection. CoRR abs/2210.06512 (2022) - 2021
- [i1]Hangjie Ji, Kyle J. Lafata, Yvonne M. Mowery, David Brizel, Andrea L. Bertozzi, Fang-Fang Yin, Chunhao Wang:
Post-Radiotherapy PET Image Outcome Prediction by Deep Learning under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application. CoRR abs/2105.10650 (2021)
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last updated on 2025-10-31 22:14 CET by the dblp team
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