Synthetic NSCLC Patient Records with Genomic Markers

ANODE-OncoGen High-Fidelity Synthetic Records provide a high-density .jsonl collection integrating clinical history with deep genomic markers for Non-Small Cell Lung Cancer. The dataset was created by AnodeAI and was last updated in March 2026.

Use Cases

• Predict cancer progression using integrated clinical history and genomic marker features.
• Train models for patient stratification based on synthetic deep genomic markers and administrative metadata.
• Benchmark synthetic data generation methods for EHR and genomics integration using the high-fidelity patient records.

Strengths

• High-fidelity synthetic records designed to integrate clinical and genomic data.
• Dataset includes a full feature specification covering administrative metadata and deep genomic markers.

Limitations

• The dataset is entirely synthetic, which may limit direct applicability to real-world clinical prediction tasks.
• Specific row counts, column counts, and sample sizes are unknown from the provided description.

Provenance

Source

AnodeAI

Collection Method

Synthetic data generation for Non-Small Cell Lung Cancer patient records.

Freshness

Last updated on 2026-03-15.

Geography

Regionus (suggested by platform tags).