From e7c3a785a2ceec5cea31f7338998d41478cc017a Mon Sep 17 00:00:00 2001 From: bartoszkochanski <68783122+bartoszkochanski@users.noreply.github.com> Date: Tue, 19 Nov 2024 11:27:44 +0100 Subject: [PATCH] Add 04.11.2024 presentation --- .../README.md | 11 +++++++++++ ...er_of_Spatial_and_Temporal_Information.pdf | Bin 0 -> 2592314 bytes README.md | 2 +- 3 files changed, 12 insertions(+), 1 deletion(-) create mode 100644 2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/README.md create mode 100644 2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/Unlocking_the_Power_of_Spatial_and_Temporal_Information.pdf diff --git a/2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/README.md b/2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/README.md new file mode 100644 index 0000000..6b82d47 --- /dev/null +++ b/2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/README.md @@ -0,0 +1,11 @@ +# Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training + +## Abstract + +We will discuss pre-training multimodal vision-language models for applications in computer-aided radiology. The multimodal models we will examine are trained jointly on raw medical images and corresponding free-text radiology reports. Radiology reports, generated abundantly within typical clinical workflows, serve as a valuable source of medical image annotations but have yet to be fully leveraged in modeling efforts. + +I will present a [recent ICML 2024 conference paper](https://icml.cc/virtual/2024/poster/34857) that addresses this issue. I will begin with examples to illustrate the rationale for developing multimodal models in radiology and provide an overview of recent work and public dataset that form the basis of this research. Then, I will detail the paper’s main contributions: (1) extending the multimodal framework to account for multiple representations of anatomy in chest radiographs, and (2) advancing temporal modeling of longitudinal data. + +## Source paper + +[Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training](https://arxiv.org/abs/2405.19654) \ No newline at end of file diff --git a/2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/Unlocking_the_Power_of_Spatial_and_Temporal_Information.pdf b/2024/2024_11_04_Unlocking_the_Power_of_Spatial_and_Temporal_Information/Unlocking_the_Power_of_Spatial_and_Temporal_Information.pdf new file mode 100644 index 0000000000000000000000000000000000000000..59c96a52d981df55e8220dc42c6b2007a77fa1a3 GIT binary patch literal 2592314 zcmdSA1yo$iwk}LUfCLBuf`kNz#ad#&qIKe%*ySux)I|K_3!5v;hcFx|p z`<#2;``@`^yuSy7UQ)H@H>GCHs`WKMicf%&mWt^mET97Xc?nC4OM`2!ZS)eBot;|F 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