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08/03/2023
The Capability of Large Language Models to Measure Psychiatric Functioning
The current work investigates the capability of Large language models (L...
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07/05/2023
Evaluating AI systems under uncertain ground truth: a case study in dermatology
For safety, AI systems in health undergo thorough evaluations before dep...
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12/26/2022
Large Language Models Encode Clinical Knowledge
Large language models (LLMs) have demonstrated impressive capabilities i...
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07/21/2022
Detecting and Preventing Shortcut Learning for Fair Medical AI using Shortcut Testing (ShorT)
Machine learning (ML) holds great promise for improving healthcare, but ...
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05/19/2022
Robust and Efficient Medical Imaging with Self-Supervision
Recent progress in Medical Artificial Intelligence (AI) has delivered sy...
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02/02/2022
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?
Fairness and robustness are often considered as orthogonal dimensions wh...
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06/16/2021
Best of both worlds: local and global explanations with human-understandable concepts
Interpretability techniques aim to provide the rationale behind a model'...
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04/08/2021
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
We develop and rigorously evaluate a deep learning based system that can...
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01/14/2021
Supervised Transfer Learning at Scale for Medical Imaging
Transfer learning is a standard technique to improve performance on task...
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01/13/2021
Big Self-Supervised Models Advance Medical Image Classification
Self-supervised pretraining followed by supervised fine-tuning has seen ...
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11/06/2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
ML models often exhibit unexpectedly poor behavior when they are deploye...
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07/10/2020
Contrastive Training for Improved Out-of-Distribution Detection
Reliable detection of out-of-distribution (OOD) inputs is increasingly u...
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09/12/2018