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Continuing Professional Development (CPD)
CICM
Lectures – Category 2A: Passive Group Learning - 1 point per hour
ANZCA
Lectures/presentations & webinars
Participants in the ANZCA and FPM CPD program may claim these webinars/seminars under the Knowledge and skills activity ‘Learning sessions’ at 1 credit per hour.
Clinical Innovation, Research & Collaboration at JR Analytics
At JR Analytics, we believe meaningful digital health innovation must be grounded in real-world clinical practice and developed through close collaboration with healthcare services, academic institutions, and industry partners. Our work focuses on identifying practical challenges in emergency, pre-hospital, and critical care settings and exploring digital approaches that support safer, more effective clinical decision-making.
JR Analytics is founded and led by a clinician with over two decades of experience in intensive care and retrieval medicine. Our innovation activities are informed by direct frontline practice, with a strong emphasis on clinical relevance, usability, governance, and alignment with established guidelines and real-world workflows.
Active Research Areas
Our current research and innovation activities focus on clinically grounded digital solutions in high-acuity environments, including:
- AI-assisted interpretation of thromboelastometry (ROTEM) traces to support haemostasis decision-making
- Digital pre-hospital documentation and workflow optimisation to improve structured data capture and continuity of care
- Development and evaluation of AI-assisted emergency department (ED) triage models using presenting complaints and structured vital signs to explore prediction of triage acuity and support emergency care workflows
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Development of sepsis-focused clinical digital twin frameworks using MIMIC ICU data to model patient trajectories, monitor treatment responses, and explore personalised decision-support opportunities in critical care
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Collaborative research in digital health, critical care informatics, and AI-enabled clinical workflow innovation
ClinAI – Artificial Intelligence for Healthcare (Coming Soon)
ClinAI is JR Analytics' developing platform for translating healthcare artificial intelligence from research into clinical practice. Rather than focusing on building a single AI model, ClinAI provides the infrastructure, governance, and collaborative environment needed to support the complete AI lifecycle.
ClinAI is designed to bring together clinicians, researchers, healthcare organisations, and industry partners to develop, validate, implement, and continuously evaluate AI solutions using real-world clinical data.
How ClinAI Works
Data Integration
Secure integration of clinical datasets from hospitals, research databases, and public repositories to support AI development and validation.
AI Development
Development of machine learning and deep learning models for clinical decision support using structured and time-series healthcare data.
Clinical Validation
Independent validation of AI models using Australian healthcare datasets to assess performance, generalisability, and clinical relevance.
Governance & Safety
Support for clinical governance, explainability, model monitoring, and responsible AI implementation aligned with healthcare standards.
Implementation
Integration of validated AI models into clinical workflows and digital health platforms, supporting pilot studies and real-world evaluation.
Continuous Learning
Ongoing monitoring, refinement, and re-validation of AI systems as new data becomes available, ensuring models remain safe and clinically relevant.