AutoMRAI: A Cloud-Based Platform for Multi-Omics Integration and Mendelian Randomization

AutoMRAI is an AI-augmented, cloud-based platform designed to advance causal inference in biomedical research by integrating multi-omics data with automated Mendelian Randomization (MR) and Structural Equation Modeling (SEM). By combining diverse biological layers—including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics—AutoMRAI enables researchers to uncover hidden biological pathways and complex interactions that drive disease mechanisms and clinical outcomes.

The platform supports widely used MR methods such as Inverse-Variance Weighted (IVW), MR-Egger, Weighted Median, and MR-PRESSO, while also providing SEM-based causal discovery tools for mediation and pathway analysis. Through an intuitive web interface, AutoMRAI automates data preparation, model fitting, and visualization, making advanced causal inference approaches accessible to clinicians, biostatisticians, and translational researchers. By bridging multi-omics data integration with interpretable AI, AutoMRAI provides a scalable solution for precision medicine and systems biology research.

Project Page: https://mrai.globalstatsol.com

ClinicalStatAI: A Cloud-Based, AI-Augmented Platform for Accessible Survival Analysis in Healthcare

ClinicalStatAI is an AI-powered, cloud-based platform developed to make advanced survival analysis accessible to healthcare professionals without requiring statistical or coding expertise. Designed in response to the growing need for interpretable analytics from electronic health records (EHRs) and real-world datasets, ClinicalStatAI integrates traditional survival models—including Cox regression, Weibull, and Kaplan-Meier—with intelligent, automated interpretation and report generation. Through a user-friendly web interface, the platform enables clinicians and researchers to perform time-to-event analyses with ease, enhancing decision-making in clinical research and care planning. As a proof-of-concept, the system demonstrates scalability, security, and usability, positioning it for broader testing, funding opportunities, and future deployment across healthcare systems.

Project Page: https://stai.globalstatsol.com

NeuroBridge: A Scalable and Intelligent Digital Cognitive Assessment Platform for Mild Cognitive Impairment and Dementia

NeuroBridge is a platform-driven digital infrastructure designed to unify cognitive testing, quantitative modeling, and electronic health record (EHR) integration within an interoperable, regulatory-compliant framework. Built on a modular Flask architecture, it comprises four layers: a secure web-based clinician–patient interface; a cognitive assessment engine hosting validated tasks across multiple domains; an analytical layer employing classical survival models (Cox, Weibull, Log-Normal) for individualized risk prediction; and an EHR integration layer based on FHIR/HL7 standards for bidirectional data exchange. Proof-of-concept testing with simulated patient data demonstrated real-time task delivery, automated scoring, pseudonymized data transmission, and EHR mapping of structured FHIR observations. NeuroBridge establishes a scalable foundation for longitudinal cognitive monitoring, multimodal data integration, and precision-based dementia risk prediction in clinical and research environments.

Project Page: https://dem.globalstatsol.com

GEN-CREATE: AI-Powered Data Storytelling for Genomic and Health

The GEN-CREATE project, led by GLOBALSTAT INTELLIGENCE SOLUTIONS LTD, will develop a powerful new digital platform that helps transform complex health and genomic data into creative, accessible, and engaging stories. Using a combination of artificial intelligence (AI), advanced statistics, and visual storytelling, the platform will empower content creators, educators, public health organisations, and science communicators to make sense of important health data and share it with a wider audience in innovative ways.