DBDebwashis Borman

Wearable Frailty Prediction (LFI)

Predicting the Liver Frailty Index from wearable accelerometer data — with Hannover Medical School.

Machine LearningTime SeriesPython

Overview

Built and benchmarked sequence models (BiLSTM, Transformer, TCN) on accelerometer data from wearable devices to predict the Liver Frailty Index for cirrhosis patients. Deployed the best-performing model as a Streamlit web app for clinical evaluation.

Key Highlights

  • BiLSTM / Transformer / TCN baselines on wearable accelerometer signals
  • Streamlit app shipped for clinician-facing evaluation
  • Collaboration with Hannover Medical School

Tech Stack

PythonPyTorchStreamlitscikit-learn

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