Classification of Ciliary Motion with 3D Convolutional Neural Networks. - Charles Lu 001; Shannon Quinn (ACM Southeast Regional Conference, 2017)

Stacked Neural Networks for end-to-end ciliary motion analysis. - Charles Lu 001; Maurice Marx; Maliha Zahid; Cecilia W. Lo; Chakra Chennubhotla 001; Shannon P. Quinn (CoRR, 2018)

An Overview and Case Study of the Clinical AI Model Development Life Cycle for Healthcare Systems. - Charles Lu 001; Julia Strout; Romane Gauriau; Bradley Wright; Fabiola Bezerra De Carvalho Marcruz; Varun Buch; Katherine P. Andriole (CoRR, 2020)

"Name that manufacturer". Relating image acquisition bias with task complexity when training deep learning models: experiments on head CT. - Giorgio Pietro Biondetti; Romane Gauriau; Christopher P. Bridge; Charles Lu 001; Katherine P. Andriole (CoRR, 2020)

Addressing catastrophic forgetting for medical domain expansion. - Sharut Gupta; Praveer Singh; Ken Chang; Liangqiong Qu; Mehak Aggarwal; Nishanth Thumbavanam Arun; Ashwin Vaswani; Shruti Raghavan; Vibha Agarwal; Mishka Gidwani; Katharina Hoebel; Jay B. Patel; et al. (CoRR, 2021)

Evaluating subgroup disparity using epistemic uncertainty in mammography. - Charles Lu 001; Andréanne Lemay; Katharina Hoebel; Jayashree Kalpathy-Cramer (CoRR, 2021)

Deploying clinical machine learning? Consider the following... - Charles Lu 001; Ken Chang; Praveer Singh; Stuart R. Pomerantz; Sean Doyle; Sujay Kakarmath; Christopher P. Bridge; Jayashree Kalpathy-Cramer (CoRR, 2021)

Distribution-Free Federated Learning with Conformal Predictions. - Charles Lu 001; Jayashree Kalpathy-Cramer (CoRR, 2021)

Fair Conformal Predictors for Applications in Medical Imaging. - Charles Lu 001; Andréanne Lemay; Ken Chang; Katharina Höbel; Jayashree Kalpathy-Cramer (AAAI, 2022)

Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets. - Charles Lu 001; Anastasios N. Angelopoulos; Stuart R. Pomerantz (MICCAI (8), 2022)

Three Applications of Conformal Prediction for Rating Breast Density in Mammography. - Charles Lu 001; Ken Chang; Praveer Singh; Jayashree Kalpathy-Cramer (CoRR, 2022)

Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction. - Charles Lu 001; Syed Rakin Ahmed; Praveer Singh; Jayashree Kalpathy-Cramer (CoRR, 2022)

Federated Conformal Predictors for Distributed Uncertainty Quantification. - Charles Lu 001; Yaodong Yu; Sai Praneeth Karimireddy; Michael I. Jordan; Ramesh Raskar (ICML, 2023)

Overcoming Trust and Incentive Barriers in Decentralized AI. - Abhishek Singh 005; Charles Lu 001; Ramesh Raskar (CogMI, 2024)

Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion. - Sharut Gupta; Ken Chang; Liangqiong Qu; Aakanksha Rana; Syed Rakin Ahmed; Mehak Aggarwal; Nishanth Thumbavanam Arun; Ashwin Vaswani; Shruti Raghavan; Vibha Agarwal; Mishka Gidwani; Katharina Hoebel; et al. (AIPAD/PILM@MICCAI, 2024)

Data Acquisition via Experimental Design for Data Markets. - Charles Lu 001; Baihe Huang; Sai Praneeth Karimireddy; Praneeth Vepakomma; Michael I. Jordan; Ramesh Raskar (NeurIPS, 2024)

Data Acquisition via Experimental Design for Decentralized Data Markets. - Charles Lu 001; Baihe Huang; Sai Praneeth Karimireddy; Praneeth Vepakomma; Michael I. Jordan; Ramesh Raskar (CoRR, 2024)

Data Measurements for Decentralized Data Markets. - Charles Lu 001; Mohammad Mohammadi Amiri; Ramesh Raskar (CoRR, 2024)

Privacy preservation for federated learning in health care. - Sarthak Pati; Sourav Kumar; Amokh Varma; Brandon Edwards; Charles Lu 001; Liangqiong Qu; Justin J. Wang; Anantharaman Lakshminarayanan; Shih-han Wang; Micah J. Sheller; Ken Chang; Praveer Singh; et al. (Patterns, 2024)