Jinjoo Shim
Jinjoo Shim
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1.Digital biomarker for longevity & Healthspan
Applying AI/ML and statistical methods for predicting biological age and healthspan using wearable data
May 3, 2024
2.Explainable AI in biological age estimation
Applying SHAP (SHapley Additive exPlanations) method to identify factors influencing biological age using wearable data
May 3, 2024
3.Digital phenotyping to demonstrate the impact of circadian aging using wearable data
Enhancing digital phenotyping through the application of AI/ML and statistical models to demonstrate using wearable, time-series data
May 3, 2024
4.Model-driven and data-driven disease classification
Using AI/ML (CNN, LSTM, RF, DT, etc.) and statistical models (cosinor, SSA) to longitudinal, time-series physical activity data to classify different diseases
May 3, 2024
Comparative Efficacy of Commercial Wearables for Circadian Rhythm Home Monitoring from Activity, Heart Rate, and Core Body Temperature
Circadian rhythms govern biological patterns that follow a 24-hour cycle. Dysfunctions in circadian rhythms can contribute to various …
Fan Wu
,
Patrick Langer
,
Jinjoo Shim
,
Elgar Fleisch
,
Filipe Barata
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