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README.md
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This dataset is a large-scale collection of
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It consists of real-world MRI data where radiological reports indicate the presence of diseases, abnormalities, or pathological conditions. These findings may include tumors, lesions, infections, degenerative changes, or other clinically significant observations.
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The dataset captures authentic imaging characteristics such as scanner variability, acquisition protocols, and patient positioning, along with detailed clinical narratives. This makes it highly valuable for building accurate, scalable, and production-ready AI systems for medical diagnosis and imaging analysis.
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Additionally, this dataset can be used in pipelines for Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows.
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**Key Use Cases**
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-Multi-modal learning (image + text)
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-Diagnostic AI model training
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**Dataset Specification**
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-Modality: MRI (Magnetic Resonance Imaging)
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-Type: Medical images with abnormal findings
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-Data Source: Clinical MRI reports
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-Body Regions: Brain, Spine, Abdomen, etc.
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-Data Nature: Real-world clinical data
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-Patients: 30,818
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-Images: 23,239,044
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**Value of This Dataset**
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size_categories:
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- 100K<n<1M
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**This dataset is a large-scale collection of MRI (Magnetic Resonance Imaging) reports with confirmed clinical findings, containing data from 53,852 patients and 29,028,321 medical images, designed to support the development and training of advanced healthcare AI, medical imaging, diagnostic AI, and clinical NLP systems.**
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It consists of real-world MRI data where radiological reports indicate the presence of diseases, abnormalities, or pathological conditions. These findings may include tumors, lesions, infections, degenerative changes, or other clinically significant observations.
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The dataset captures authentic imaging characteristics such as scanner variability, acquisition protocols, and patient positioning, along with detailed clinical narratives. This makes it highly valuable for building accurate, scalable, and production-ready AI systems for medical diagnosis and imaging analysis.
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Additionally, this dataset can be used in pipelines for Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows.
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**Dataset Specification**
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-Patients: 53,852
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-Images: 29,028,321
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-Modality: MRI (Magnetic Resonance Imaging)
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-Type: Medical images with abnormal findings
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-Data Source: Clinical MRI reports
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-Body Regions: Brain, Spine, Abdomen, etc.
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-Data Nature: Real-world clinical data
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**Key Use Cases**
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-Multi-modal learning (image + text)
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-Diagnostic AI model training
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**Value of This Dataset**
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