commit 185e247243baf2a5363cf030eb949af11322ebb8
parent 1fe5a09e71f7f073f996ec4a95aac5353db01ef3
Author: Silas Brack <silasbrack@gmail.com>
Date: Tue, 7 Apr 2026 15:54:00 +0200
feat: add optimized alerts
Diffstat:
1 file changed, 3 insertions(+), 1 deletion(-)
diff --git a/main.typ b/main.typ
@@ -97,7 +97,9 @@
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- Computer vision, transformers, forecasting, embedded machine learning
+ - Performed an in-depth analysis of thousands of falls to understand which factors are related to falls and how they can be better prevented. Preprocessed data to account for various biases and confounders.
+ - Trained various models to predict falls, though ended up converging on a two-stage model with one brute-force optimisation step and one logistic regression to forecast fall likelihood across different time horizons. This approach was chosen to maximise interpretability and actionability for care staff.
+ - Based on my analysis and modelling, I designed, implemented and rolled out a new notification system based on resident actions rather than whereabouts, along with an automatic fall risk prediction model which led to a notification volume drop of 56% (mitigating spammy alerts) and a fall rate reduction of 66%. First-hand user feedback on this feature has also been collected and has been consistently positive.
]
)
],
