Jayashree Kalpathy-Cramer

MONAI: An open-source framework for deep learning in healthcare

2022 · 432 Zit. · arXiv (Cornell University)

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

2025 · 302 Zit. · BMJ

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

2023 · 38 Zit. · arXiv (Cornell University)

Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

2023 · 29 Zit. · British Journal of Radiology

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons

2023 · 9 Zit. · Journal of Medical Imaging

Environment scan of generative AI infrastructure for clinical and translational science

2025 · 8 Zit. · npj Health Systems

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

2021 · 7 Zit. · arXiv (Cornell University)

Improving the repeatability of deep learning models with Monte Carlo dropout

2022 · 5 Zit. · arXiv (Cornell University)

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

2022 · 3 Zit. · arXiv (Cornell University)

MIDRC mRALE Mastermind Grand Challenge: AI to predict COVID severity on chest radiographs

2025 · 1 Zit. · Journal of Medical Imaging

Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center Open Data Commons

2023 · 1 Zit. · arXiv (Cornell University)

Assessing the (Un)Trustworthiness of Saliency Maps for Localizing\n Abnormalities in Medical Imaging

2020 · 0 Zit. · arXiv (Cornell University)