commit 9121d191950e35075d2c249ae4a1351f67d30a22
parent c1b70f61c4421e880032ece034c960c4871781d5
Author: Silas Brack <silasbrack@gmail.com>
Date: Thu, 16 Apr 2026 07:59:53 +0200
fix: correct numbers
Diffstat:
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/main.typ b/main.typ
@@ -94,7 +94,7 @@
text(size: 10pt)[
- 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.
+ - 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 30%. First-hand user feedback on this feature has also been collected and has been consistently positive.
],
)
],
