Tzu-Ming Harry Hsu
Cited by
Cited by
Measuring the effects of non-identical data distribution for federated visual classification
TMH Hsu, H Qi, M Brown
arXiv preprint arXiv:1909.06335, 2019
Clinically Accurate Chest X-Ray Report Generation
G Liu, TMH Hsu, M McDermott, W Boag, WH Weng, P Szolovits, ...
Machine Learning for Healthcare Conference, 249-269, 2019
3d-aware scene manipulation via inverse graphics
S Yao, TM Hsu, JY Zhu, J Wu, A Torralba, B Freeman, J Tenenbaum
Advances in neural information processing systems 31, 2018
Federated visual classification with real-world data distribution
TMH Hsu, H Qi, M Brown
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Unsupervised domain adaptation with imbalanced cross-domain data
T Ming Harry Hsu, W Yu Chen, CA Hou, YH Hubert Tsai, YR Yeh, ...
Proceedings of the IEEE International Conference on Computer Vision, 4121-4129, 2015
Learning food quality and safety from wireless stickers
U Ha, Y Ma, Z Zhong, TM Hsu, F Adib
Proceedings of the 17th ACM workshop on hot topics in networks, 106-112, 2018
Transfer Neural Trees for Heterogeneous Domain Adaptation
WY Chen, TMH Hsu, YHH Tsai, YCF Wang, MS Chen
Computer Vision (ECCV), 2016 European Conference on, 2016
Baselines for chest x-ray report generation
W Boag, TMH Hsu, M McDermott, G Berner, E Alesentzer, P Szolovits
Machine learning for health workshop, 126-140, 2020
Unsupervised Multimodal Representation Learning across Medical Images and Reports
TMH Hsu, WH Weng, W Boag, M McDermott, P Szolovits
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018, 2018
Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output
MBA McDermott, TMH Hsu, WH Weng, M Ghassemi, P Szolovits
Machine Learning for Healthcare Conference, 913-927, 2020
Artificial intelligence to assess body composition on routine abdominal CT scans and predict mortality in pancreatic cancer–A recipe for your local application
TMH Hsu, K Schawkat, SJ Berkowitz, JL Wei, A Makoyeva, K Legare, ...
European journal of radiology 142, 109834, 2021
Visceral adiposity and severe COVID-19 disease: application of an artificial intelligence algorithm to improve clinical risk prediction
A Goehler, TMH Hsu, JA Seiglie, MJ Siedner, J Lo, V Triant, J Hsu, ...
Open forum infectious diseases 8 (7), ofab275, 2021
Transfer neural trees: Semi-supervised heterogeneous domain adaptation and beyond
WY Chen, TMH Hsu, YHH Tsai, MS Chen, YCF Wang
IEEE Transactions on Image Processing 28 (9), 4620-4633, 2019
Three-dimensional neural network to automatically assess liver tumor burden change on consecutive liver MRIs
A Goehler, TMH Hsu, R Lacson, I Gujrathi, R Hashemi, G Chlebus, ...
Journal of the American College of Radiology 17 (11), 1475-1484, 2020
Adversarial contrastive pre-training for protein sequences
M McDermott, B Yap, H Hsu, D Jin, P Szolovits
arXiv preprint arXiv:2102.00466, 2021
Positional assessment of lower third molar and mandibular canal using explainable artificial intelligence
S Kempers, P van Lierop, TMH Hsu, DA Moin, S Bergé, H Ghaeminia, T Xi, ...
Journal of Dentistry 133, 104519, 2023
Emulating clinical diagnostic reasoning for jaw cysts with machine learning
B Feher, U Kuchler, F Schwendicke, L Schneider, ...
Diagnostics 12 (8), 1968, 2022
Intra-oral scan segmentation using deep learning
S Vinayahalingam, S Kempers, J Schoep, TMH Hsu, DA Moin, ...
BMC Oral Health 23 (1), 643, 2023
DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
TMH Hsu, YCC Wang
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
Automatic longitudinal assessment of tumor responses
Massachusetts Institute of Technology, 2020
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