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Dataset and Readme upload.

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Data_ReadMe.md ADDED
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+ Dataset Name: LitMedImage – literature-derived Medical vs. Non-Medical Image Dataset
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+
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+ -------------------
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+ Description:
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+ -------------------
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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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+
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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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+
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+ -------------------
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+ Label Definitions:
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+ -------------------
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+
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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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+
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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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+
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+ -------------------
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+ Task Instruction:
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+ -------------------
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+
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+ Given an image, classify whether it is a MEDICAL image or a NON-MEDICAL image.
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+
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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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+
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+ Intended Use:
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+
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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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+
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+ Citation:
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+ [To be added]
LitMedImage_Test.csv ADDED
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