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Research Areas

Computational BiologySingle-cell, bulk RNA-seq, spatial, and biomarkers
CardiologyCardiovascular signals, cohorts, and interpretationImmunologyImmune cell states, signaling networks, and repertoire dynamicsNeurologyBrain connectivity, functional imaging, and electrophysiologyOncologyTumor microenvironment, immune response, mutations, and survivalPathologyWhole-slide imaging, tissue quantification, and spatial pathology

Application

Documentation

Documentation

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AI interpretation

Interpretation is an optional layer after metrics exist. Every output cites computed values from completed runs — the LLM does not invent numbers.

Prerequisites

  • Completed HRV, cohort summary, baroreflex, or related pipeline run
  • Ollama credentials configured in backend-analysis (see repo root ai.md)

Descriptive mode

Plain-language summary of what the metrics suggest physiologically.

Available for:

  • Single HRV run (includes SQI and arrhythmia burden when present)
  • Cohort comparison (group differences with p-values and group means)
  • Subject hub (summary across available modalities)

Where to launch:

  • Run detail page → Interpret
  • Cohort workspace → Interpret
  • Subject hub → Interpret

Mechanistic mode

Cross-domain hypotheses when multiple metric domains are present on a subject:

  • Autonomic (HRV)
  • Hemodynamic (BP variability, dipping)
  • Baroreflex sensitivity
  • Respiration / RSA
  • Rhythm burden

Outputs include pathway tags (for example autonomic, hemodynamic), confidence levels, and linked metric badges. Falls back to descriptive mode if only one domain is available.

Where to launch:

  • Subject hub → Interpret (mechanistic)
  • Run detail (when multimodal context exists)
  • Cohort outlier panel

Guardrails

Every interpretation artifact includes:

  • Research / non-clinical disclaimer
  • Metric citation validation (numbers must match run artifacts)
  • Automatic caveats for low SQI, high artifact rate, or missing modalities

Copy text or export JSON from the interpret panel.

What interpretation does not do

  • Diagnose conditions or recommend treatment
  • Replace expert review of signal quality
  • Compute new metrics — it explains metrics already in artifacts