Healthcare AI Datasets for Clinical & LLM Training
Collection
Sample dataset from an enterprise-grade medical corpus built for clinical AI, diagnosis support, and healthcare LLM training. • 12 items • Updated • 1
Dataset Description:
This dataset is a large-scale collection of X-ray (Radiography) reports without clinical findings, designed to support the development of robust medical imaging and diagnostic AI systems focused on normal baseline learning.
The dataset captures authentic imaging characteristics such as scanner variability, acquisition protocols, and patient positioning, along with clinical narratives. This ensures high-quality, real-world data suitable for building accurate and scalable AI systems. Additionally, this dataset can be used in pipelines for Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows, enabling models to better distinguish between normal and abnormal cases and reduce false positives.
Key Use Cases
-Baseline learning for diagnostic models
-False positive reduction
-Medical image segmentation
-Clinical decision support systems
-Radiology report generation
-Model validation and calibration
Dataset Specification
-Modality: X-ray (Radiography)
-Type: Medical images without clinical findings
-Data Source: Clinical X-ray reports
-Body Regions: Chest, Limbs, Spine, Abdomen, etc.
-Data Nature: Real-world clinical data
-Patients: 775
-Images: 775
Value of This Dataset
-Improves model specificity and reduces false alarms
-Supports binary and multi-class classification tasks
-Essential for anomaly detection systems
-Helps build clinically safe AI solutions
-Supports real-world healthcare deployment
Basic JSON Schema
{
"patient_id": "string",
"image": "image",
"view_position": "string",
"body_part": "string",
"sex": "string",
"age": "string",
"study_uid": "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: vipul@infobay.ai
- Downloads last month
- 9