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- 2020
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Mark
Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
(
- Contribution to journal › Article
- 2019
-
Mark
Variational auto-encoders with Student’s t-prior
2019) 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems
(
- Contribution to journal › Article
-
Mark
Artificial neural network models to predict nodal status in clinically node-negative breast cancer
(
- Contribution to journal › Article
-
Mark
Human Leukocyte Antigen-Based Risk Stratification in Heart Transplant Recipients-Implications for Targeted Surveillance
(
- Contribution to journal › Article
- 2018
-
Mark
Improving prediction of heart transplantation outcome using deep learning techniques
2018) In Scientific Reports(
- Contribution to journal › Article
- 2017
-
Mark
Tumor tissue protein signatures reflect histological grade of breast cancer
2017) In PLoS ONE(
- Contribution to journal › Article
-
Mark
Automatic Gleason grading of H&E stained microscopic prostate images using deep convolutional neural networks
(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
3D skeletal uptake of 18F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer
(
- Contribution to journal › Article
-
Mark
Association of PET index quantifying skeletal uptake in NaF PET/CT images with overall survival in prostate cancer patients
2017) American Society of Clinical Oncology Genitourinary (ASCO GU) Cancers Symposium In Journal of Clinical Oncology 35(6 Suppl). p.178-178(
- Contribution to journal › Published meeting abstract