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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

Back to studies

Welcome

The Cardiology area of Gradient Biotech is a web workspace for multimodal cardiovascular and physiological signal research. Upload ECG, RR intervals, blood pressure, PPG, and respiration recordings; run validated pipelines; link data to subjects; compare cohorts; and generate AI-assisted interpretations grounded in computed metrics.

What you can do today

CapabilityStatus
ECG preprocessing + HRVFull workflow: upload → preprocess → metrics → waveform explorer
RR-only HRVCSV upload → compute HRV directly
PPG + PRVPreprocess PPG → pulse rate variability
Blood pressureVariability, dipping classification
Baroreflex, RSA, respirationCross-modal coupling pipelines
Cohort comparisonGroup stats, tests, outliers, batch HRV
AI interpretationDescriptive and mechanistic modes with metric citations
Risk stratification (research)Signal-derived cohort risk scores

How the product is organized

Every analysis lives inside a study. From the cardiology dashboard you create or open a study, then work through four main areas:

  1. Overview / Upload — add datasets and review study stats
  2. Dataset inspector — run pipelines, explore waveforms, view run history
  3. Subjects — import cohort metadata and link recordings to participants
  4. Cohort — compare groups, batch jobs, export charts

Pipeline jobs run asynchronously. Track progress via the Jobs panel in the navbar.

Who this is for

  • Cardiovascular researchers running HRV, telemetry, or wearable analysis without maintaining local MATLAB/Python toolchains
  • Hospital research programs processing Holter or telemetry cohorts with reproducible runs
  • Digital health teams ingesting RR or PPG exports at scale
  • Translational teams attaching outcomes metadata and comparing treatment groups

What this is not

  • Not a regulated clinical decision support device
  • Not a passive ECG viewer — waveforms support QC and context for cohort intelligence
  • Not automatic diagnosis — arrhythmia outputs are burden metrics for research

Next steps

  • Use cases — scenario guides for Holter HRV, wearable cohorts, multimodal autonomic profiling, and cohort endpoints
  • Quick start — run your first ECG analysis in minutes
  • Key concepts — studies, datasets, runs, and subjects
  • Study workflow — how the main sections fit together