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Found 6 papers, 1 papers with code
Merlin: A Vision Language Foundation Model for 3D Computed Tomography
However, current medical VLMs are generally limited to 2D images and short reports, and do not leverage electronic health record (EHR) data for supervision.
Phasor-Driven Acceleration for FFT-based CNNs
Recent research in deep learning (DL) has investigated the use of the Fast Fourier Transform (FFT) to accelerate the computations involved in Convolutional Neural Networks (CNNs) by replacing spatial convolution with element-wise multiplications on the spectral domain.
AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments
Evaluating large language models (LLM) in clinical scenarios is crucial to assessing their potential clinical utility.
AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT
While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoregional patient cohorts with less diverse data sources.
Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography
Extracting quantitative body composition measures manually from CT scans is a cumbersome and time-consuming task.
DiffML: End-to-end Differentiable ML Pipelines
In this paper, we present our vision of differentiable ML pipelines called DiffML to automate the construction of ML pipelines in an end-to-end fashion.
