Precision Decisions.
Digital Twins.

Empowering clinicians, medical researchers, and students to safely simulate Glioblastoma outcomes and optimize data-driven therapeutic strategies before real-world application.

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Core Systems.

Engineered for precision. Four tightly integrated modules forming a comprehensive decision-support pipeline.

Patient Digital Twins

Input patient KPS scores and age data to construct a 1:1 computational replica of the patient context, calculating a dynamic safety priority for objective analysis.

KPS IntegrationSafety Prioritization

Treatment Simulation

Simulate progressive treatments across a 12-week timeline. Set clear clinical goals—like a 50% tumor volume reduction—and track exact efficacy rates.

12-Week ModelingVolumetric Tracking

Spatial Visualization

Render anatomically precise 3D brain regions from the cerebellum anterior lobe to the cerebrum. Interactively map tumor boundaries and track reduction rates.

WebGL RenderingSpatial Mapping

Therapy Ranking

Provide ranked treatment options based on real-world clinical databases. The algorithm computes an overall safety and efficacy score for personalized care.

Intervention DatabaseMolecular Targets

Technical Stack.

A resilient, full-stack architecture prioritizing performance and strict clinical data compliance.

Client Infrastructure

React 18

Functional architecture & hooks

Three.js

Hardware-accelerated 3D rendering

Component System

Custom interface library

REST Interface
Server Architecture

Flask

RESTful API endpoints

NumPy / Pandas

Numerical array processing

Scikit-learn

Random Forest ensemble models

React 18
Three.js
WebGL
Flask
Python 3.8+
Scikit-learn
NumPy
Pandas
TCGA Integration

Validated Metrics.

Integrating real clinical data from the National Cancer Institute. Tested and trained across the TCGA, TCIA, and UPEN datasets.

0+
Total Patients
Tested & Trained
0%
Target Reduction
Tumor Volume Tracking
0
Week Simulation
Timeline Tracking
0
Major Datasets
TCGA, TCIA, UPEN

Model Architecture Validation

Survival Predictor
82%
Random Forest Regressor
Progression Model
78%
Random Forest Regressor
Toxicity Classifier
85%
Random Forest Ensemble
Production Ready

System Integration.

Join the cohort of medical researchers and clinicians accelerating oncology pipelines with CerebraX's digital twin simulation environments.

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Regulatory Notice: CerebraX is an investigational clinical decision support software recognized and approved by personnel at the University of Illinois Health and the Illinois Department of Public Health (IDPH). Not an FDA-cleared diagnostic device for direct patient care without institutional review.