Search Results for author: Charles Lu

Found 14 papers, 3 papers with code

Data Measurements for Decentralized Data Markets

no code implementations6 Jun 2024 Charles Lu, Mohammad Mohammadi Amiri, Ramesh Raskar

Decentralized data markets can provide more equitable forms of data acquisition for machine learning.

Federated Conformal Predictors for Distributed Uncertainty Quantification

1 code implementation27 May 2023 Charles Lu, Yaodong Yu, Sai Praneeth Karimireddy, Michael I. Jordan, Ramesh Raskar

Conformal prediction is emerging as a popular paradigm for providing rigorous uncertainty quantification in machine learning since it can be easily applied as a post-processing step to already trained models.

Conformal Prediction Federated Learning +1

Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction

no code implementations12 Jul 2022 Charles Lu, Syed Rakin Ahmed, Praveer Singh, Jayashree Kalpathy-Cramer

Estimating the test performance of software AI-based medical devices under distribution shifts is crucial for evaluating the safety, efficiency, and usability prior to clinical deployment.

Conformal Prediction

Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets

1 code implementation5 Jul 2022 Charles Lu, Anastasios N. Angelopoulos, Stuart Pomerantz

Our work applies these new uncertainty quantification methods -- specifically conformal prediction -- to a deep-learning model for grading the severity of spinal stenosis in lumbar spine MRI.

Conformal Prediction Prediction Intervals +2

Three Applications of Conformal Prediction for Rating Breast Density in Mammography

no code implementations23 Jun 2022 Charles Lu, Ken Chang, Praveer Singh, Jayashree Kalpathy-Cramer

Breast cancer is the most common cancers and early detection from mammography screening is crucial in improving patient outcomes.

Conformal Prediction Fairness +1

Distribution-Free Federated Learning with Conformal Predictions

no code implementations14 Oct 2021 Charles Lu, Jayasheree Kalpathy-Cramer

Federated learning has attracted considerable interest for collaborative machine learning in healthcare to leverage separate institutional datasets while maintaining patient privacy.

Decision Making Federated Learning +1

Deploying clinical machine learning? Consider the following...

no code implementations14 Sep 2021 Charles Lu, Ken Chang, Praveer Singh, Stuart Pomerantz, Sean Doyle, Sujay Kakarmath, Christopher Bridge, Jayashree Kalpathy-Cramer

Despite the intense attention and considerable investment into clinical machine learning research, relatively few applications have been deployed at a large-scale in a real-world clinical environment.

BIG-bench Machine Learning Position +1

Evaluating subgroup disparity using epistemic uncertainty in mammography

no code implementations6 Jul 2021 Charles Lu, Andreanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer

As machine learning (ML) continue to be integrated into healthcare systems that affect clinical decision making, new strategies will need to be incorporated in order to effectively detect and evaluate subgroup disparities to ensure accountability and generalizability in clinical workflows.

BIG-bench Machine Learning Decision Making +1

Stacked Neural Networks for end-to-end ciliary motion analysis

no code implementations20 Mar 2018 Charles Lu, M. Marx, M. Zahid, C. W. Lo, C. Chennubhotla, S. P. Quinn

We find that the combination of segmentation and classification networks in a single pipeline yields performance comparable to existing computational pipelines, while providing the additional benefit of an end-to-end, fully-automated analysis toolbox for ciliary motion.

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