Search Results for author:
Found 4 papers, 2 papers with code
BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
Therefore, training an effective generalist biomedical model requires high-quality multimodal data, such as parallel image-text pairs.
Ranked #3 on
Medical Visual Question Answering
on SLAKE-English
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision
Results: We conduct an extensive study on 135, 107 patients from the cancer registry of a large integrated delivery network (IDN) comprising healthcare systems in five western US states.
Time-varying Autoregression with Low Rank Tensors
In each time window, we assume the data follow a linear model parameterized by a system matrix, and we model this stack of potentially different system matrices as a low rank tensor.
AJILE Movement Prediction: Multimodal Deep Learning for Natural Human Neural Recordings and Video
This paper describes our approach to detect and to predict natural human arm movements in the future, a key challenge in brain computer interfacing that has never before been attempted.
