Multi-task learning framework
Multi-task learning framework has been studied in 1 paper since 2025: none in people yet; 1 in the past year. No study of it in people or animals has been published yet. The newest paper, Dec 12, 2025: “Multi-Task Learning for Gait Phase and Gait Cycle Percentage Prediction With Wearable Sensors in Frail Older Adults”.
1 paper studies it1 findingUpdated
- In silico1
What did studies of Multi-task learning framework find?
1Studies of Multi-task learning framework measured 1 outcome; the most studied are gait phase prediction accuracy (1 study).
Gait phase prediction accuracy
upin silico1
1 study
Gait phase prediction accuracy
upin silico1
Multi-task learning framework improves gait phase prediction accuracy in silico (accuracy of 97.56%, MAE of 0.0397).
“demonstrating that our framework significantly outperforms single-task learning and hard parameter-sharing baselines, achieving an accuracy of 97.56% and a Mean Absolute Error (MAE) of 0.0397.”
In silicofrailn = 158
IEEE journal of biomedical and health informatics
Latest
1 paper in 12 monthsIEEE Journal of Biomedical and Health Informatics
Multi-Task Learning for Gait Phase and Gait Cycle Percentage Prediction With Wearable Sensors in Frail Older Adults
Computational studyBiomarkers