Extraction Module
The Extraction Module is divided into four components. The first three are pages dedicated to simple extraction processes on various data types (images, text notes, and time series) using pre-trained models and/or Python libraries. The fourth component is MEDimage, which is the implementation of a Python open-source package designed for medical image processing and radiomics features extraction.
In the video below, the "HAIM study" refers to the study of Soenksen et al.
Content
00:00 Overview
00:50 Extraction Images
04:24 Extraction Time Series
08:29 Extraction Text
10:48 Last Word
Data
Physionet : https://physionet.org/
MIMIC-IV Demo database : https://physionet.org/content/mimic-iv-demo/2.2/
MIMIC-IV-Note : https://physionet.org/content/mimic-iv-note/2.2/
MIMIC-IV-CXR : https://physionet.org/content/mimic-cxr-jpg/2.0.0/
Study of Soenksen et al. : https://www.nature.com/articles/s41746-022-00689-4
Extraction tools
TorchXRayVision : https://github.com/mlmed/torchxrayvision
TSfresh : https://tsfresh.readthedocs.io
BioBERT : https://arxiv.org/abs/1901.08746
BioBERT weights : https://github.com/EmilyAlsentzer/clinicalBERT
pageImage Extraction PagepageText Extraction PagepageTime Series Extraction PagepageMEDimage
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