Clusters of interacting methods for improving health services network design and delivery. Includes Forrester quotes on statistical vs SD methods and the Modeller's dilemma. Simplified version of IM-14982 combined with IM-17598 and IM-9773

This project proposes the design, development, and evaluation of a bio-cybernetic monitoring system (BCIMS) and clinician dashboard for early detection of cardio-renal complications in people with diabetes admitted or followed at Defence Forces Memorial Hospitals. The system integrates continuous and episodic physiological inputs (CGM, BP, heart rate/ECG, urine albumin, serum creatinine/eGFR, fluid balance, medication records) with rule-based and machine-learning algorithms to produce validated signals, clinician workflows, audit trails, and semi-automated closed-loop nephroprotection interventions staged after dashboard validation.

This project proposes the design, development, and evaluation of a bio-cybernetic monitoring system (BCIMS) and clinician dashboard for early detection of cardio-renal complications in people with diabetes admitted or followed at Defence Forces Memorial Hospitals. The system integrates continuous and episodic physiological inputs (CGM, BP, heart rate/ECG, urine albumin, serum creatinine/eGFR, fluid balance, medication records) with rule-based and machine-learning algorithms to produce validated signals, clinician workflows, audit trails, and semi-automated closed-loop nephroprotection interventions staged after dashboard validation.