Foundation Model Forecasting — Oura Digital Twin

Oura Ring Gen 4 sensor data — not clinical measurementsN=1 case study — not validated for clinical decisionsHEV diagnosed Mar 18; interpret findings cautiously in this Day 55 post-ruxolitinib window

Foundation Model

Abnormal

unavailable

ModuleNotFoundError: No module named 'torch'

RMSSD MAE

Abnormal

N/Ams

90% PI coverage: N/A%

HR MAE

Abnormal

N/Abpm

90% PI coverage: N/A%

Feb 9 Chronos Holdout

Abnormal

Not run

Chronos retrospective holdout unavailable

Ruxolitinib Start

Info

16. mar 2026

March Ensemble

ARIMA only

0 HIGH confidence anomalies | Feb 9 not detected

1. Nightly RMSSD and HR - Chronos unavailable

Chronos could not be loaded in this run, so nightly foundation-model forecast charts were skipped. Statistical baseline outputs remain below.

2. Continuous HR - Chronos unavailable

Hourly Chronos analysis was skipped because the Chronos pipeline was unavailable.

3. Statistical Baseline - ARIMA

Chronos was unavailable, so the consensus view is reduced to the statistical baseline only.

4. Feb 9 Retrospective Validation

Retrospective Chronos validation was skipped because the foundation model was unavailable.

Feb 9 Detection Summary

Method	Series	Detected?	Residual
Chronos retrospective not available in this run.

Prospective March ensemble HIGH-confidence anomalies: None detected
Feb 9 in March ensemble consensus: No

5. Pre vs Post Ruxolitinib Regime Analysis

Pre/post-ruxolitinib Chronos regime analysis was skipped because the foundation model was unavailable.

Detailed Metrics

Section	Metric	Value
data_range
	start	2026-01-08
	end	2026-05-09
	n_nights	122
ensemble_consensus
	error	no overlapping forecasts
statistical_hr
	model	ARIMA(0, 1, 2)
	mae	4.270
	rmse	5.493
	coverage_90ci	100.000
	n_anomalies	0
	anomaly_dates
statistical_rmssd
	model	ARIMA(0, 1, 1)
	mae	1.448
	rmse	1.843
	coverage_90ci	92.900
	n_anomalies	1
	anomaly_dates	2026-03-09

N=1 retrospective case study. All detection metrics are descriptive, not inferential. The model was trained and evaluated on a single patient's data. Validation requires an external multi-patient cohort.