Standardized schema for integrating genomics, proteomics, imaging, clinical, and behavioral health data for AI-driven preventive healthcare research.
``json`
{
"genomic_profile": {
"sample_id": "string",
"sequencing_platform": "illumina|pacbio|nanopore",
"variants": [
{
"chromosome": "string",
"position": "integer",
"ref_allele": "string",
"alt_allele": "string",
"variant_type": "snv|indel|cnv|sv",
"clinical_significance": "pathogenic|benign|uncertain",
"gene_symbol": "string",
"transcript_id": "string"
}
],
"polygenic_scores": {
"cardiovascular_risk": "float",
"diabetes_risk": "float",
"cancer_risk": "float"
}
}
}
json
{
"proteomic_profile": {
"sample_id": "string",
"assay_type": "mass_spec|immunoassay|proximity_extension",
"biomarkers": [
{
"protein_id": "string",
"uniprot_id": "string",
"concentration": "float",
"units": "ng/ml|pg/ml|relative_units",
"detection_method": "string",
"quality_score": "float"
}
],
"pathway_analysis": {
"enriched_pathways": ["string"],
"pathway_scores": {"pathway_name": "float"}
}
}
}
`
3. Clinical Data (FHIR R4 Compatible)
`json
{
"clinical_profile": {
"patient_id": "string",
"demographics": {
"age": "integer",
"sex": "male|female|other",
"ethnicity": "string",
"race": "string"
},
"vital_signs": [
{
"timestamp": "datetime",
"blood_pressure_systolic": "integer",
"blood_pressure_diastolic": "integer",
"heart_rate": "integer",
"temperature": "float",
"weight": "float",
"height": "float"
}
],
"lab_results": [
{
"test_code": "string",
"test_name": "string",
"value": "float",
"units": "string",
"reference_range": "string",
"timestamp": "datetime"
}
],
"medications": [
{
"medication_code": "string",
"medication_name": "string",
"dosage": "string",
"frequency": "string",
"start_date": "date",
"end_date": "date"
}
]
}
}
`
4. Imaging Data
`json
{
"imaging_profile": {
"study_id": "string",
"modality": "ct|mri|xray|ultrasound|pet|oct",
"body_part": "string",
"acquisition_parameters": {
"resolution": "string",
"contrast_agent": "boolean",
"acquisition_date": "datetime"
},
"image_features": {
"radiomics_features": {"feature_name": "float"},
"ai_annotations": [
{
"finding": "string",
"confidence": "float",
"bounding_box": [{"x": "float", "y": "float"}]
}
]
}
}
}
`
5. Behavioral/Lifestyle Data
`json
{
"behavioral_profile": {
"patient_id": "string",
"lifestyle_factors": {
"smoking_status": "never|former|current",
"alcohol_consumption": "none|light|moderate|heavy",
"exercise_frequency": "sedentary|light|moderate|vigorous",
"diet_pattern": "mediterranean|western|vegetarian|other"
},
"social_determinants": {
"education_level": "string",
"income_bracket": "string",
"insurance_status": "string",
"geographic_region": "string"
},
"wearable_data": [
{
"device_type": "fitbit|apple_watch|garmin|other",
"metric": "steps|heart_rate|sleep|activity",
"value": "float",
"timestamp": "datetime"
}
]
}
}
`
Data Integration Schema
Unified Patient Record
`json
{
"patient_record": {
"patient_id": "string",
"study_id": "string",
"fair_metadata": {
"persistent_identifier": "string (F1)",
"metadata_registry_url": "string (F4, A1)",
"ontologies_used": ["string (I2)"],
"data_usage_license": "string (R1.1)",
"data_provenance": "string (R1.2)"
},
"consent_status": "active|withdrawn|expired",
"data_collection_date": "datetime",
"genomic_profile": "object",
"proteomic_profile": "object",
"clinical_profile": "object",
"imaging_profile": "object",
"behavioral_profile": "object",
"longitudinal_data": [
{
"timepoint": "baseline|6month|1year|2year",
"data_snapshot": "object"
}
],
"outcomes": {
"primary_endpoints": ["string"],
"secondary_endpoints": ["string"],
"adverse_events": ["string"]
}
}
}
`
Privacy and Security Schema
De-identification Metadata
`json
{
"deidentification_metadata": {
"method": "safe_harbor|expert_determination|synthetic",
"k_anonymity": "integer",
"l_diversity": "integer",
"privacy_budget": "float",
"suppressed_fields": ["string"],
"generalized_fields": {"field_name": "generalization_level"}
}
}
`
Quality Control Schema
Data Quality Metrics
`json
{
"quality_metrics": {
"completeness": "float",
"accuracy": "float",
"consistency": "float",
"timeliness": "float",
"validity": "float",
"uniqueness": "float",
"quality_flags": ["missing_data|outlier|inconsistent|duplicate"]
}
}
``