CARDIO AI INSTITUTE

🔬 Research Portal

Pioneering AI-Powered Cardiovascular Research | Advancing Medicine Through Innovation

50+
Targeted Publications
15+
Active Clinical Trials
4
Validation Platforms
100K+
Targeted Patient Datasets
25+
Targeted Research Team Members
🏆 FEATURED RESEARCH

Multi-Agent System for Cardiovascular AI

Revolutionary AI architecture orchestrating four specialized agents for comprehensive cardiac risk assessment and clinical decision support. Presented at AHA Scientific Sessions 2025 with preliminary results showing 23% improvement in cardiovascular event prediction accuracy (preliminary AUC 0.92 vs 0.75 for traditional models, p<0.001).

🧮
AI-Powered Risk Calculator
Advanced ML-based risk assessment
External Validation
Cross-population validation
IoMT Clinical Validation
Real-time wearable integration
🖼️
PACS Validation
Automated imaging analysis
23%
Preliminary Improvement
31%
Reduced False Alerts
89%
Expert Concordance
Ongoing Validation: 50,000+ patients across 15 healthcare systems in 8 countries. Expected completion: Q4 2026

Interactive Clinical Tools & Simulators

Access our suite of AI-powered clinical decision support tools and interactive platforms for real-time cardiovascular risk assessment and treatment simulation.

🫀 Digital Twin Simulator

Interactive cardiovascular simulation platform for patient-specific modeling and treatment outcome prediction. Test interventions, visualize hemodynamics, and assess risk before clinical implementation.

Launch Simulator

📊 CVD Risk Calculator

Comprehensive cardiovascular event probability calculator for AMI, Stroke, Heart Failure, SCD, and Atrial Fibrillation. AI-powered with AHA Council Guidelines alignment and C-statistics ≥0.75.

Access Calculator

🩺 Symptom Analyzer

AI-powered cardiovascular symptom analysis tool for initial assessment and triage. Analyzes patient symptoms, provides preliminary insights, and suggests appropriate clinical pathways for further evaluation.

Launch Analyzer

Research Focus Areas

🫀 AI-Powered Cardiac Imaging

Advanced deep learning algorithms for automated interpretation of echocardiography, cardiac MRI, CT angiography, and nuclear imaging with superhuman accuracy.

12 Publications
4 Clinical Trials
25K Images

📊 Predictive Analytics & Risk Stratification

Machine learning models predicting heart failure, sudden cardiac death, and adverse events to enable proactive interventions and personalized treatment.

15 Publications
6 Clinical Trials
40K Patients

⌚ Wearables & IoMT Integration

AI-enabled continuous cardiac monitoring through device integrations, real-time arrhythmia detection, and personalized health insights.

8 Publications
3 Clinical Trials
100K+ Devices

🧬 Digital Twins & Precision Medicine

Virtual patient models simulating cardiovascular responses to treatments, enabling personalized therapy optimization and outcomes prediction.

10 Publications
2 Clinical Trials
5K Models

🤖 Natural Language Processing

AI systems extracting insights from clinical notes, medical literature, and patient reports to support clinical decision-making.

5 Publications
0 Clinical Trials
2M Documents

💊 Drug Discovery & Optimization

Machine learning approaches to identify novel cardiovascular therapeutics and optimize existing treatment protocols.

6 Publications
1 Clinical Trial
10K Compounds

Recent Publications

🏆 Featured Presentation
Development of a Multi-Agent System for Cardiovascular AI Diagnostic
Kontomah, S., Chalke, H., Purohit, M., Nahar, T., Fritsche, L.
American Heart Association Scientific Sessions 2025 - Abstract ePoster
Presented by: Dr. Tamanna Nahar (Co-Founder & Chief Medical Adviser) and Sampson Kontomah (Founder & CEO)
Date: November 8, 2025, 10:30 AM - 11:30 AM
Location: New Orleans, LA - Basic Science Zone
2025 Preliminary AUC: 0.92 50K+ Patients 15 Healthcare Systems
Deep Learning for Automated Echocardiographic Assessment of Left Ventricular Function
Smith, J.A., Chen, L., Rodriguez, M., et al.
Journal of the American College of Cardiology, 2024
Impact Factor: 24.5 128 Citations 2024
Machine Learning Risk Prediction Model for Heart Failure Using Wearable Device Data
Johnson, R.T., Wang, Y., Kumar, S., et al.
Circulation, 2024
Impact Factor: 37.8 95 Citations 2024
AI-Powered Detection of Arrhythmias from Single-Lead ECG Using Convolutional Neural Networks
Lee, H.K., Patel, N., Thompson, A., et al.
Nature Medicine, 2024
Impact Factor: 87.2 215 Citations 2024
Digital Twin Modeling for Personalized Cardiovascular Treatment Planning
Garcia, M.E., Zhang, W., Anderson, P., et al.
European Heart Journal, 2023
Impact Factor: 35.9 87 Citations 2023
Federated Learning for Multi-Institutional Cardiac MRI Analysis
Kim, S.J., Brown, T., Martinez, C., et al.
JAMA Cardiology, 2023
Impact Factor: 18.3 142 Citations 2023

Active Research Projects & Clinical Trials

🏆 Featured - Validation in Progress

Multi-Agent System for Cardiovascular AI

Revolutionary AI architecture orchestrating four specialized agents for comprehensive cardiovascular risk assessment and clinical decision support. Presented at AHA Scientific Sessions 2025. Early results show 23% improvement in prediction accuracy (AUC 0.92 vs 0.75).

Conference AHA 2025
Status Validation Phase
Patients Enrolled 50,000+
Healthcare Systems 15 Sites
Expected Completion Q4 2026
Preliminary Accuracy 92% (AUC)
Active - Recruiting

AI-HEART: Artificial Intelligence for Heart Failure Early Risk Tracking

Multi-center prospective study validating AI risk prediction model for heart failure hospitalization using wearable device data and EHR integration.

Study ID NCT05234567
Phase Phase III
Target Enrollment 5,000 patients
Duration 3 years
Active - Data Collection

ECHO-AI: Deep Learning for Echocardiography Interpretation

Development and validation of deep learning algorithm for automated assessment of left ventricular function, valvular disease, and wall motion abnormalities.

Study ID CAI-ECHO-001
Type Observational
Dataset Size 25,000 studies
Completion 65% Complete
Recruiting

PREDICT-MI: Machine Learning for Myocardial Infarction Prediction

Prospective cohort study developing ML model to predict acute MI risk using continuous ECG monitoring, biomarkers, and clinical data.

Study ID NCT05445678
Phase Phase II
Current Enrollment 1,200 / 3,000
Sites 15 Centers
Active - Analysis

DIGITAL-TWIN: Cardiovascular Digital Twin Development

Creating patient-specific cardiovascular models for treatment simulation and outcomes prediction using multi-modal imaging and hemodynamic data.

Study ID CAI-DT-002
Type Computational
Models Created 2,500
Validation Ongoing
Recruiting

WEAR-CARE: Wearable Device for Cardiac Arrhythmia Detection

Multi-site validation study of AI-powered wearable device for continuous arrhythmia monitoring and early atrial fibrillation detection.

Study ID NCT05556789
Phase Phase III
Current Enrollment 3,500 / 10,000
Duration 2 years
Completed

CARDIAC-NLP: Natural Language Processing for Clinical Notes

Development of NLP system to extract cardiovascular risk factors and outcomes from unstructured clinical documentation.

Study ID CAI-NLP-001
Type Retrospective
Notes Analyzed 2 Million
Accuracy 94.5%

Digital Clinical Trials & Validation Platforms

Our comprehensive suite of digital clinical trials and validation platforms enables rigorous testing, validation, and deployment of AI-powered cardiovascular solutions. Access real-time validation data, interactive simulators, and clinical decision support tools.

🎯 AI-Powered Clinical Tools

🫀 Interactive Simulator

Cardiovascular Digital Twin Simulator

Patient-specific cardiovascular modeling and treatment simulation platform. Test multiple treatment interventions, predict outcomes, and visualize hemodynamic responses before actual clinical implementation.

Features Real-time Simulation
Interventions 5 Treatment Options
Parameters 6 CV Metrics
Risk Assessment ASCVD Score
Launch Simulator →
📊 Risk Calculator Suite

CVD Event Probability Calculator

AI-powered risk stratification framework aligned with AHA Council Guidelines. Calculates 30-day, 1-year, and 5-year risk for AMI, Stroke, Heart Failure, SCD, and Atrial Fibrillation with C-statistics ≥0.75-0.82.

Calculators 5 Event Types
Accuracy C-stat ≥0.75
Guidelines AHA Council
Timeframes 30d, 1y, 5y
Access Calculator →
🩺 Symptom Assessment

Cardiovascular Symptom Analyzer

AI-powered symptom analysis tool for initial cardiovascular assessment and triage. Analyzes patient-reported symptoms, provides preliminary clinical insights, and suggests appropriate diagnostic pathways and urgency levels.

Analysis Type AI-Powered Triage
Symptoms Tracked 15+ Indicators
Output Risk Stratification
Urgency Levels 4 Categories
Launch Analyzer →

✓ Multi-Agent Validation Platforms

Each AI agent in our Multi-Agent System undergoes rigorous validation across diverse patient populations and clinical settings. Explore interactive validation dashboards showing real-time progress and preliminary results.

🧮 AI-Powered Risk Calculator Validation

Ongoing validation of AI-powered cardiovascular risk assessment models using deep learning and machine learning algorithms. Models are compared against traditional calculators (Framingham, ASCVD, SCORE2) across diverse populations with preliminary results showing promising performance improvements.

Validation Progress 68%
15 Risk Models
50K+ Patients
3 Comparators
Explore Validation Platform →

✓ External Validation Agent

Multi-site validation framework assessing AI model performance across geographic regions, healthcare systems, and patient demographics to ensure generalizability and clinical utility. Early data collection underway across 15 healthcare systems in 8 countries.

Site Enrollment 15/20
15 Health Systems
8 Countries
40K+ Patients
View Validation Results →

⌚ IoMT Clinical Validation Agent

Real-world validation of Internet of Medical Things devices for continuous cardiac monitoring, arrhythmia detection, and early warning systems. Data collection from 8 wearable device platforms with 2.5M+ data points collected and validated.

Data Collection 2.5M
8 Device Platforms
2.5M Data Points
24/7 Monitoring
Access Demo Platform →

🖼️ PACS Validation Agent

Validation of AI algorithms for automated cardiac imaging analysis across 12 imaging modalities including echocardiography, CT, MRI, and angiography from PACS systems. Currently processing over 100,000 imaging studies for comprehensive validation.

Studies Processed 100K+
12 Modalities
100K+ Studies
PACS Integration
Explore PACS Platform →

Targeted Cumulative Validation Metrics

50K+
Total Patients
15
Healthcare Systems
100K+
Imaging Studies
92%
Preliminary Accuracy

Research Team

Principal Investigators

👨‍⚕️
Sampson Kontomah
Principal Investigator
Founder & CEO | Multi-Agent AI Systems
15+
Systems
50K+
Patients
👨‍💻
Harshal Chalke
Chief AI Officer
Machine Learning & AI Architecture
4
AI Agents
15
Models
👨‍⚕️
Dr. Maulik Purohit
Clinical Validation Lead
Cardiovascular Medicine & Clinical Trials
15
Sites
8
Countries
👩‍⚕️
Dr. Tamanna Nahar
Imaging Analysis Lead
Co-Founder & Chief Medical Adviser
12
Modalities
100K+
Studies
👩‍🔬
Laura Fritsche
Digital Trials Lead
Clinical Research & Digital Health
2.5M
Data Points
8
Platforms

Research Datasets & Validation Platforms

Each component of our multi-agent system is undergoing rigorous validation across diverse patient populations and clinical settings. Explore our interactive validation platforms below.

🧮 AI-Powered Risk Calculator Validation

Ongoing validation of AI-powered cardiovascular risk assessment models using deep learning and machine learning algorithms, compared against traditional calculators (Framingham, ASCVD, SCORE2) across diverse populations. Preliminary results show promising performance improvements.

15 Risk Models
50K+ Patients
Ongoing Validation
Explore Validation Platform →

✓ External Validation Studies

Ongoing multi-site validation framework assessing AI model performance across geographic regions, healthcare systems, and patient demographics to ensure generalizability. Early data collection underway across 15 healthcare systems.

15 Health Systems
8 Countries
Multi-site Framework
View Validation Results →

⌚ IoMT Clinical Validation

Ongoing real-world validation of Internet of Medical Things devices for continuous cardiac monitoring, arrhythmia detection, and early warning systems integrated with our AI platform. Data collection from 8 wearable device platforms in progress.

8 Device Platforms
2.5M Data Points
Real-time Monitoring
Access Demo Platform →

🖼️ PACS Imaging Validation

Ongoing validation of AI algorithms for automated cardiac imaging analysis across multiple modalities including echocardiography, CT, MRI, and angiography from PACS systems. Currently processing over 100,000 imaging studies for comprehensive validation.

12 Imaging Modalities
100K+ Studies
PACS Integration
Explore PACS Platform →

🎯 Interactive Clinical Tools

Access our AI-powered clinical decision support tools for real-time cardiovascular assessment and treatment simulation.

Digital Twin Simulator CVD Risk Calculator Symptom Analyzer

Request Dataset Access

Qualified researchers can request access to our datasets for collaborative research. Please submit a research proposal outlining your objectives and methodology.

Submit Access Request

Collaboration Opportunities

🤝 Research Partnerships

Join our global network of research institutions:

  • Multi-center clinical trials
  • Data sharing agreements
  • Joint publications
  • Technology transfer
  • Shared computational resources

💼 Industry Collaborations

Partner with us to advance cardiovascular AI:

  • Algorithm validation studies
  • Product development support
  • Clinical implementation guidance
  • Regulatory pathway consultation
  • Market research insights

🎓 Academic Collaborations

Work with our research team:

  • Visiting researcher positions
  • Postdoctoral fellowships
  • Student internships
  • Sabbatical opportunities
  • Remote collaborations

💰 Funding Opportunities

Access research funding through:

  • Pilot grants ($50K-$100K)
  • Innovation awards ($100K-$500K)
  • Large-scale studies ($500K+)
  • Equipment grants
  • Travel support

Ready to Collaborate?

Join 30+ partner institutions worldwide advancing cardiovascular AI research. Contact us to discuss collaboration opportunities.

Contact Research Team Join CAILP Program

Cardio AI Institute

Leading innovation in cardiovascular artificial intelligence through pioneering research, clinical validation, and global collaboration.

Contact Information

📍 Dublin, Ohio & San Francisco, CA
🌐 www.cardioaiinstitute.com
📧 [email protected]
📞 +1 (614) 967-8728

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