11 citations · 20 across the 5 of their papers we have counts for
5 papers
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Peter Brodeur, Jacob M. Koshy, Anil Palepu +45
Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and management conversations in simulated settings. Translating these systems into clin…
Unlocking Accuracy and Fairness in Differentially Private Image Classification
Leonard Berrada, Soham De, Judy Hanwen Shen +6
Privacy-preserving machine learning aims to train models on private data without leaking sensitive information. Differential privacy (DP) is considered the gold standard framework…
Conformal prediction under ambiguous ground truth
David Stutz, Abhijit Guha Roy, Tatiana Matejovicova +3
Conformal Prediction (CP) allows to perform rigorous uncertainty quantification by constructing a prediction set satisfying for a user-chose…
Evaluating AI systems under uncertain ground truth: a case study in dermatology
David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy +17
For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However…
Learning Optimal Conformal Classifiers
David Stutz, Krishnamurthy, Dvijotham +2
Modern deep learning based classifiers show very high accuracy on test data but this does not provide sufficient guarantees for safe deployment, especially in high-stake AI applica…