QuantumLearning Machines

Clinical Nursing Scenarios

P3 clinical presence layer -- 5 rotations x 3 scenarios, live rendered clinical state with gate wiring.

88HR bpm
96SpO2 %
132/78NIBP MAP 96.0
16RR /min
37.0Temp C
alert
t = 0 min

The quiet fall -- R1-S1

78 years old, post-fall, admitted for observation. The chart says stable. The clock disagrees -- quietly. Everything on the monitor is computed from one patient model.

0all parameters in band

Gate 1: Recognize (CJMM: recognize cues)

What is the earliest deterioration cue on this patient?

Gate 2: Analyze (CJMM: analyze cues)

EWS is climbing. How do you use it?

Gate 3: Prioritize (CJMM: prioritize hypotheses)

New confusion appears at t=40 in this post-fall patient. What is the top hypothesis?

Gate 4: Take action (CJMM: take action)

Each scenario has pinned clinical data -- no random values. All arithmetic is audited inline. Gate verdicts tag the CJMM layer and NURS misconception code confronted. 15 scenarios across 5 rotations, complete.