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Found 6 papers, 4 papers with code
Exploring the Boundaries of GPT-4 in Radiology
In this paper, we focus on assessing the performance of GPT-4, the most capable LLM so far, on the text-based applications for radiology reports, comparing against state-of-the-art (SOTA) radiology-specific models.
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Prior work in biomedical VLP has mostly relied on the alignment of single image and report pairs even though clinical notes commonly refer to prior images.
Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing
We release a new dataset with locally-aligned phrase grounding annotations by radiologists to facilitate the study of complex semantic modelling in biomedical vision--language processing.
Predicting the impact of treatments over time with uncertainty aware neural differential equations
In this work, we propose Counterfactual ODE (CF-ODE), a novel method to predict the impact of treatments continuously over time using Neural Ordinary Differential Equations equipped with uncertainty estimates.
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit
In this work, we propose a new deep learning model based on the combination of temporal convolution and pointwise (1x1) convolution, to solve the length of stay prediction task on the eICU and MIMIC-IV critical care datasets.
Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks
The pressure of ever-increasing patient demand and budget restrictions make hospital bed management a daily challenge for clinical staff.
