Shih-Cheng Huang

According to our database, Shih-Cheng Huang authored at least 27 papers between 2018 and 2024.

Collaborative distances:

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

2024

Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging.

Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, Hany Hassan Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Serena Yeung-Levy, Curtis P. Langlotz, Sheng Wang, Hoifung Poon

CoRR, 2024

2023

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging.

Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou

IEEE Trans. Medical Imaging, 2023

Self-supervised learning for medical image classification: a systematic review and implementation guidelines.

Shih-Cheng Huang, Anuj Pareek, Malte Jensen, Matthew P. Lungren, Serena Yeung, Akshay S. Chaudhari

npj Digit. Medicine, 2023

Author Correction: Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.

Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad

npj Digit. Medicine, 2023

INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis.

Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Matthew P. Lungren, Curtis P. Langlotz, Serena Yeung, Nigam H. Shah, Jason A. Fries

CoRR, 2023

Chat Vector: A Simple Approach to Equip LLMs With New Language Chat Capabilities.

Shih-Cheng Huang, Pin-Zu Li, Yu-Chi Hsu, Kuang-Ming Chen, Yu-Tung Lin, Shih-Kai Hsiao, Richard Tzong-Han Tsai, Hung-yi Lee

CoRR, 2023

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors.

Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang, Oishi Banerjee, Farah Dadabhoy, Veeral Vipin Mehta, Ryan Wonhee Han, Fang Cao, Raja R. Narayan, Errol Colak, Adewole S. Adamson, Laura Heacock, Geoffrey H. Tison, Alex Tamkin, Pranav Rajpurkar

CoRR, 2023

LOVM: Language-Only Vision Model Selection.

Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang, Serena Yeung

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms.

Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg, Chia-Chun Chiang, Curtis P. Langlotz, Matthew P. Lungren, Serena Yeung, Nigam Shah, Jason Alan Fries

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Video pretraining advances 3D deep learning on chest CT tasks.

Alexander Ke, Shih-Cheng Huang, Chloe P. O'Connell, Michal Klimont, Serena Yeung, Pranav Rajpurkar

Proceedings of the Medical Imaging with Deep Learning, 2023

Diagnosing and Rectifying Vision Models using Language.

Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Automatic Lung Nodule Segmentation and Intra-Nodular Heterogeneity Image Generation.

Jiangdian Song, Shih-Cheng Huang, Brendan Kelly, Guanqun Liao, Jingyun Shi, Ning Wu, Weimin Li, Zaiyi Liu, Lei Cui, Matthew P. Lungren, Michael E. Moseley, Peng Gao, Jie Tian, Kristen W. Yeom

IEEE J. Biomed. Health Informatics, 2022

Prostate cancer therapy personalization via multi-modal deep learning on randomized phase III clinical trials.

Andre Esteva, Jean Feng, Douwe van der Wal, Shih-Cheng Huang, Jeffry P. Simko, Sandy Devries, Emmalyn Chen, Edward M. Schaeffer, Todd M. Morgan, Yilun Sun, Amirata Ghorbani, Nikhil Naik, Dhruv Nathawani, Richard Socher, Jeff M. Michalski, Mack Roach, Thomas M. Pisansky, Jedidiah M. Monson, Farah Naz, James Wallace, Michelle J. Ferguson, Jean-Paul Bahary, James Zou, Matthew P. Lungren, Serena Yeung, Ashley E. Ross, Michael J. Kucharczyk, Luis Souhami, Leslie Ballas, Christopher A. Peters, Sandy Liu, Alexander G. Balogh, Pamela D. Randolph-Jackson, David L. Schwartz, Michael R. Girvigian, Naoyuki G. Saito, Adam Raben, Rachel A. Rabinovitch, Khalil Katato, Howard M. Sandler, Phuoc T. Tran, Daniel E. Spratt, Stephanie Pugh, Felix Y. Feng, Osama Mohamad

npj Digit. Medicine, 2022

General Framework for Self-Supervised Model Priming for Parameter-Efficient Fine-tuning.

Shih-Cheng Huang, Shih-Heng Wang, Min-Han Shih, Saurav Sahay, Hung-yi Lee

CoRR, 2022

Few-shot Prompting Towards Controllable Response Generation.

Hsuan Su, Po-Han Chi, Shih-Cheng Huang, Ho-Lam Chung, Saurav Sahay, Shang-Tse Chen, Hung-Yi Lee

CoRR, 2022

Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation.

Yuhui Zhang, Shih-Cheng Huang, Zhengping Zhou, Matthew P. Lungren, Serena Yeung

Proceedings of the Machine Learning for Health, 2022

2021

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR.

Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries, Alaa Youssef, Timothy J. Amrhein, Marcello Chang, Imon Banerjee, Daniel L. Rubin, Lei Xing, Nigam Shah, Matthew P. Lungren

CoRR, 2021

OncoNet: Weakly Supervised Siamese Network to automate cancer treatment response assessment between longitudinal FDG PET/CT examinations.

Anirudh Joshi, Sabri Eyuboglu, Shih-Cheng Huang, Jared Dunnmon, Arjun Soin, Guido A. Davidzon, Akshay Chaudhari, Matthew P. Lungren

CoRR, 2021

Reading Race: AI Recognises Patient's Racial Identity In Medical Images.

Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P. Lungren, Lyle J. Palmer, Brandon J. Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W. Gichoya

CoRR, 2021

GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition.

Shih-Cheng Huang, Liyue Shen, Matthew P. Lungren, Serena Yeung

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines.

Shih-Cheng Huang, Anuj Pareek, Saeed Seyyedi, Imon Banerjee, Matthew P. Lungren

npj Digit. Medicine, 2020

Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Christopher Chute, Robyn L. Ball, Norah Borus, Andrew Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren

npj Digit. Medicine, 2020

PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Christopher Chute, Robyn L. Ball, Norah Borus, Andrew Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren

npj Digit. Medicine, 2020

Bio-Magnetic/Eddy-Current Sensor Design for Biological Object Detection.

Chun-Yeon Lin, Yi-Chin Wu, Yuan-Liang Chen, Shih-Cheng Huang

Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2020

2019

Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks.

Adam Rule, Amanda Birmingham, Cristal Zuñiga, Ilkay Altintas, Shih-Cheng Huang, Rob Knight, Niema Moshiri, Mai H. Nguyen, Sara Brin Rosenthal, Fernando Pérez, Peter W. Rose

PLoS Comput. Biol., 2019

Distributed Current Source Method for Modeling Magnetic and Eddy-Current Fields induced in Biological Object.

Chun-Yeon Lin, Kok-Meng Lee, Yuan-Liang Chen, Shih-Cheng Huang

Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2019

2018

Ten Simple Rules for Reproducible Research in Jupyter Notebooks.

Adam Rule, Amanda Birmingham, Cristal Zuñiga, Ilkay Altintas, Shih-Cheng Huang, Rob Knight, Niema Moshiri, Mai H. Nguyen, Sara Brin Rosenthal, Fernando Pérez, Peter W. Rose

CoRR, 2018