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Fore❤️Care
Fore❤️Care: Student Research Opportunities
Fore❤️Care: Student Research Opportunities
Fore❤️Care is seeking motivated students to join our privacy-first AI project dedicated to cardiovascular risk prediction and prevention. Our research specifically addresses reducing health disparities, such as the higher heart failure rates observed among African American communities.
Key Research Area
Key Research Area
On-Device AI & Computer Vision: Developing image processing and machine learning for tasks like food photo calorie analysis.
Secure Edge Computing: Implementing federated learning and blockchain-integrated edge-cloud systems for resilient predictions.
Multimodal Sensor Fusion: Real-time integration of wearable data, including ECG, Blood Pressure, SpO2, and physical activity.
Geospatial & Social Determinants: GIS integration to analyze environmental factors like air quality and neighborhood resource access.
Clinical NLP & LLM: Utilizing Large Language Models for natural-language explanations, conversational coaching, and empathetic alerts.
Equity-Driven Dashboards: Creating public health dashboards and context-aware alerts to provide equity-driven health insights.
Opportunities by Academic Level
Opportunities by Academic Level
PhD & Masters (Graduate Research Assistant)
Secure Architectures: Designing federated learning and blockchain protocols for high-security, privacy-preserving predictions.
LLM Innovation: Leading the development of complex LLM enhancements for clinical geospatial reasoning and empathetic patient coaching.
Undergraduate (Technical Research Intership)
Data Pipelines: Developing real-time pipelines for wearable sensor fusion and on-device machine learning models.
GIS Mapping: Assisting with GIS integration to map environmental social determinants of health.
Middle & High School (Junior Research Scholar)
AI Foundations: Gaining early exposure to AI basics, including how on-device imaging promotes youth nutrition and food security.
Community Wellness: Supporting the development of public health dashboards and "no-fire" culinary wellness initiatives.
GIS Mapping: Assisting with GIS integration to map environmental social determinants of health.
How to Apply:
Interested candidates should submit a CV and a statement of interest highlighting relevant experience in AI, healthcare, or community-driven research.
Project Summary
Heart failure occurs when the heart cannot pump enough blood and oxygen to meet the body's needs, leading to serious health challenges and reduced quality of life. Recent estimates indicate that approximately 6.7 million adults in the United States (aged 20 and older) are living with heart failure, with projections showing continued growth to 8.7 million by 2030 and up to 11.4 million by 2050.
Disparities remain stark: African American individuals face a disproportionately higher burden, including earlier onset, higher incidence, prevalence, and mortality rates from heart failure and related conditions (e.g., high blood pressure, stroke, diabetes) compared to other racial groups. These inequities highlight the urgent need for equitable, proactive tools that address both individual and community-level risks.
In response, Fore❤️Care is a privacy-first mobile app that empowers users — especially those in underserved communities — to predict and prevent cardiovascular risks through advanced, secure AI. We propose a multi-factor risk prediction framework powered by a federated learning-based, blockchain-integrated edge-cloud paradigm. This approach ensures resiliency, high accuracy, robust security, and strong privacy protection by keeping sensitive health data on-device or distributed, while enabling collaborative model improvement without centralizing personal information.
System Architecture
Project Objectives – Fore❤️Care
Project Objectives – Fore❤️Care
Fore❤️Care empowers users with privacy-first AI to predict and prevent cardiovascular risks, now enhanced by Large Language Models (LLMs) for more natural, personalized, and educational interactions while advancing digital health research.
Build and deploy the Fore❤️Care mobile app for accurate cardiovascular risk prediction using BP measurements, Heart rate data, calorie intake estimated via on-device food photo analysis and deliver intuitive, personalized heart-health recommendations tailored to individual risk profiles & daily habits and lifestyle
Validate the federated edge-cloud prediction framework through extensive simulation studies for accuracy, scalability, and robustness testing
Enable continuous cardiovascular monitoring with wearables
Incorporate GIS for environmental & social risk context
Fuse sensor data with GIS in advanced predictive models
Integrate Large Language Models (LLMs) for enhanced user interaction & personalization
Provide geospatial visualizations and dashboards
Launch context-aware alert systems with LLM-enhanced notifications
Support public health research & policy with LLM-augmented insights
Create and share interactive educational content to raise heart health awareness & promote prevention strategies online
Publication – Fore❤️Care
U Ghosh, D Das, N Shillingford, P Chatterjee, "Federated Edge-Cloud Framework for Heart Disease Risk Prediction Using Blockchain", in the Proceedings of 6th IFIP International Internet Of Things (IFIP-IoT) Conference, 2023, Nov 2-3, 2023, Dallas-Fort Worth Metroplex, Texas, USA.
Team Members – Fore❤️Care
Uttam Ghosh, PhD
Pushpita Chatterjee, PhD
Debashis Das, PhD
Tenicka Norwood
Charnisha Azubuike
KeiToniya Tate
Testbed, Mobile Application (Android and iOS) Fore❤️Care: TBD
Presentation Slides and Video : Github Repository
News
Our paper " EHR Security and Privacy Aspects: A Systematic Review" is accepted as a regular paper in IFIP IoT 2023. Congratulations to my research intern Mr. Sudip Barik.
Our paper "Federated Edge-Cloud Framework for Heart Disease Risk Prediction Using Blockchain" is accepted as a regular paper in IFIP IoT 2023. Congratulations Dr. Debashis Das and the entire team.
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