The dynamic nature of emotions in language learning context: Theory, method, and analysis

P Wang, L Ganushchak, C Welie… - Educational Psychology …, 2024 - Springer
In current research, emotions in language use situations are often examined only at their
starting and ending points, akin to observing the beginning and end of a wave, while …

Machine learning applications in preventive healthcare: A systematic literature review on predictive analytics of disease comorbidity from multiple perspectives

XU Duo, XU Zeshui - Artificial Intelligence in Medicine, 2024 - Elsevier
Artificial intelligence is constantly revolutionizing biomedical research and healthcare
management. Disease comorbidity is a major threat to the quality of life for susceptible …

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19

M Van der Schaar, AM Alaa, A Floto, A Gimson… - Machine Learning, 2021 - Springer
The COVID-19 global pandemic is a threat not only to the health of millions of individuals,
but also to the stability of infrastructure and economies around the world. The disease will …

Neural graphical modelling in continuous-time: consistency guarantees and algorithms

A Bellot, K Branson, M van der Schaar - ar** for cold-start diagnosis prediction in healthcare data
Y Tan, C Yang, X Wei, C Chen, W Liu, L Li… - Proceedings of the 45th …, 2022 - dl.acm.org
Cold-start diagnosis prediction is a challenging task for AI in healthcare, where often only a
few visits per patient and a few observations per disease can be exploited. Although meta …

[PDF][PDF] D-code: Discovering closed-form odes from observed trajectories

Z Qian, K Kacprzyk, M van der Schaar - International Conference on …, 2022 - par.nsf.gov
For centuries, scientists have manually designed closed-form ordinary differential equations
(ODEs) to model dynamical systems. An automated tool to distill closedform ODEs from …

A systematic review of networks for prognostic prediction of health outcomes and diagnostic prediction of health conditions within Electronic Health Records

Z Hancox, A Pang, PG Conaghan, SR Kingsbury… - Artificial Intelligence in …, 2024 - Elsevier
Background and objective: Using graph theory, Electronic Health Records (EHRs) can be
represented graphically to exploit the relational dependencies of the multiple information …

Temporal logic point processes

S Li, L Wang, R Zhang, X Chang, X Liu… - International …, 2020 - proceedings.mlr.press
We propose a modeling framework for event data and aim to answer questions such
as\emph {when} and\emph {why} the next event would happen. Our proposed model excels …

Interpretable machine learning for high-dimensional trajectories of aging health

S Farrell, A Mitnitski, K Rockwood… - PLoS Computational …, 2022 - journals.plos.org
We have built a computational model for individual aging trajectories of health and survival,
which contains physical, functional, and biological variables, and is conditioned on …