Generating synthetic multidimensional molecular time series data for machine learning: considerations

G An, C Cockrell - Frontiers in Systems Biology, 2023 - frontiersin.org
The use of synthetic data is recognized as a crucial step in the development of neural
network-based Artificial Intelligence (AI) systems. While the methods for generating synthetic …

[HTML][HTML] A human digital twin approach for fatigue-aware task planning in human-robot collaborative assembly

Y You, B Cai, DT Pham, Y Liu, Z Ji - Computers & Industrial Engineering, 2025 - Elsevier
Human-robot collaboration (HRC) has emerged as a pivotal paradigm in manufacturing,
integrating the strengths of both human and robot capabilities. Neglecting human physical …

Increased femoral anteversion does not lead to increased joint forces during gait in a cohort of adolescent patients

N Alexander, R Brunner, J Cip, E Viehweger… - … in Bioengineering and …, 2022 - frontiersin.org
Orthopedic complications were previously reported for patients with increased femoral
anteversion. A more comprehensive analysis of the influence of increased femoral …

Shallow learning vs. deep learning in engineering applications

F Jafari, K Moradi, Q Shafiee - Shallow Learning vs. Deep Learning: A …, 2024 - Springer
In this chapter, the application of machine learning (ML) in various engineering domains has
ushered in transformative advancements, offering solutions to intricate problems and paving …

Integrating musculoskeletal simulation and machine learning: a hybrid approach for personalized ankle-foot exoskeleton assistance strategies

X Zhang, S Li, Z Ying, L Shu, N Sugita - Frontiers in Bioengineering …, 2024 - frontiersin.org
Introduction: Lower limb exoskeletons have shown considerable potential in assisting
human walking, particularly by reducing metabolic cost (MC), leading to a surge of interest in …

[HTML][HTML] Glenohumeral joint force prediction with deep learning

P Eghbali, F Becce, P Goetti, P Büchler, DP Pioletti… - Journal of …, 2024 - Elsevier
Deep learning models (DLM) are efficient replacements for computationally intensive
optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive …