InfoBayAI/Ultrasound-USG-Reports-Dataset

Dataset Description:

This dataset is a large-scale collection of ultrasound clinical reports, containing data from 2,748 patients, designed to support the development and training of advanced healthcare AI, medical imaging, diagnostic AI, and clinical NLP systems.

The dataset captures real-world variability in radiology reporting styles, anatomical descriptions, and diagnostic terminology used in ultrasound examinations. It includes unstructured textual findings, enabling models to learn how clinicians describe both normal and abnormal observations. This makes the dataset highly valuable for building accurate and scalable clinical language understanding systems. Additionally, this dataset can be used in pipelines for Supervised Fine-Tuning (SFT), helping models better interpret imaging findings and improve performance in downstream diagnostic tasks.

Key Use Cases

-Named entity recognition (NER) in ultrasound reports
-Findings classification (normal vs abnormal)
-Automated report summarization
-Clinical decision support systems
-Model validation and calibration

Value of This Dataset

-Enables learning of real clinical reporting patterns
-Improves NLP model accuracy in medical text understanding
-Supports classification and information extraction tasks
-Helps detect abnormalities from textual findings
-Enhances reliability of clinical AI systems
-Useful for real-world healthcare applications

Basic JSON Schema

{
  "patient_id": "string",
  "findings": "string"
}

Data Creation

Procured through formal agreements and generated in the ordinary course of business.

Considerations

This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website InfoBay.AI or contact us directly.

-Ph: (91) 8303174762
-Email: datareq@infobay.ai