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DualBeat

DualBeat is an AI-powered cardiac intelligence platform designed to help clinicians evaluate the complete patient before making heart-related treatment decisions.

Core trick

Parses uploaded PDFs, ECG images, and vitals into a canonical cardiac state, then drives a pressure-volume simulation with each number linked to its source.

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Description

DualBeat is an AI-powered cardiac intelligence platform designed to help clinicians evaluate the complete patient before making heart-related treatment decisions. The system combines cardiovascular data, multimorbidity analysis, medication-safety checks, clinical guidelines, ECG signals, CT imaging, and digital-twin simulation to identify risks that may be missed when care is focused on only one organ. The DualBeat logo represents two connected perspectives of cardiac care: the patient’s heart and the wider clinical context surrounding it. The dual-tone heart symbolizes the interaction between cardiovascular treatment and the rest of the body, while the central ECG waveform represents continuous analysis, clinical monitoring, and evidence-driven decision support. The orange and white color palette communicates energy, urgency, clarity, trust, and modern medical innovation. DualBeat does not autonomously diagnose or prescribe treatment. Instead, it provides clinicians with evidence-linked warnings, cross-organ medication conflicts, missing-information alerts, alternative options for consideration, and transparent simulation results. Its purpose is to support safer, more informed, and more personalized cardiac-care decisions. Tagline: Smart Care. Stronger Hearts.
Shradhapujari/DualBeat★ 10 forksPythonCreated Jul 18, 2026 · last push Jul 19, 2026

README excerpt

# DualBeat

**An auditable, multi-agent cardiac digital twin.** Upload the cardiac evidence you already have — a discharge PDF, an ECG image or CSV, an echo/MRI still, or just structured vitals — and DualBeat builds an explainable physiological model of the heart: a canonical cardiac state, a beating 3D twin with anatomically-localized findings, a pressure–volume simulation, and bounded recovery forecasts. Every number shows where it came from.

> **Educational simulation only.** DualBeat is **not a medical device**. It does not diagnose, prescribe, triage, or recommend treatment. Every output is a simulated, educational estimate.

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## Why this matters

Clinicians and trainees are surrounded by numbers (EF, QTc, CO, MAP) and by tools that produce more numbers — but almost none of those tools let you see *where a number came from*, *what it implies physiologically*, or *what happens next under a different load*. Two failure modes dominate:

1. **Static calculators** give you one formula in isolation. They can't relate EF to afterload, localize a regional change to a coronary territory, or project a recovery trajectory.
2. **Black-box medical LLMs** will happily *invent* an ejection fraction, hide their reasoning, and drift into diagnostic language. Nothing about the output is auditable, and that is exactly what makes it unusable in a clinical setting.

DualBeat is built around the conviction that **a model is only useful to a clinician if its every value is traceable, its 

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