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--- |
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license: cc-by-3.0 |
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task_categories: |
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- zero-shot-classification |
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language: |
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- en |
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pretty_name: LitMedImage |
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size_categories: |
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- 10K<n<100K |
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--- |
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Dataset Name: LitMedImage – literature-derived Medical vs. Non-Medical Image Dataset |
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Description: |
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------------------- |
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LitMedImage is a curated dataset of biomedical literature figures labeled as MEDICAL or NON-MEDICAL. The dataset is built from images extracted from PubMed Central Open Access (PMC-OA) articles and includes corresponding captions and parsed image metadata. Labels were generated using a large language model (LLM) following strict imaging definitions. This dataset is intended for research in figure classification, document parsing, and biomedical vision-language models. |
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Columns: |
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PMCID: PubMed Central article identifier (e.g., PMC1234567) |
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Image_num: Index of the image within the article |
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Online_file_path: Direct file path to the image under https://ftp.ncbi.nlm.nih.gov/pub/pmc/ |
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Image_info_Cleaned: Parsed metadata describing the image contents |
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Caption_Clean: Cleaned image caption from the original publication |
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label: Binary classification label ("yes" for MEDICAL images, "no" for NON-MEDICAL images) |
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Label Definitions: |
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Label = "yes" (MEDICAL) |
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Images that belong to clinical or biomedical imaging modalities, including: |
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Radiology, Echocardiography, Dermoscopy, Histopathology, X-ray (Radiography), CT, MRI, Ultrasound, Nuclear Medicine (PET, SPECT, PET-CT, PET-MRI), Optical Imaging, Thermography, Elastography, Mammography, Digital Breast Tomosynthesis, Fluoroscopy, Clinical Imaging |
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Label = "no" (NON-MEDICAL) |
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Images that are statistical plots or schematic illustrations, including: |
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Bar charts, Histograms, Line graphs, Scatter or Bubble plots, Pie or Donut charts, Area charts, Heatmaps, Box or Violin plots, Radar or Spider charts, Treemaps, Network graphs, Drawings, Conceptual diagrams |
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Task Instruction: |
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Given an image, classify whether it is a MEDICAL image or a NON-MEDICAL image. |
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Data Source: |
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All images originate from the PubMed Central Open Access Subset via the public FTP archive at: |
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https://ftp.ncbi.nlm.nih.gov/pub/pmc/ |
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Intended Use: |
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- Binary image classification (medical vs. non-medical) |
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- Multimodal image + caption classification |
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- Figure filtering for automated document processing |
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- Pre-filtering figures for vision-language model training or inference |
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Citation: |
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[To be added] |
