Spatiotemporal data mining: a survey on challenges and open problems

A Hamdi, K Shaban, A Erradi, A Mohamed… - Artificial Intelligence …, 2022 - Springer
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

Artificial intelligence accelerates multi-modal biomedical process: A Survey

J Li, X Han, Y Qin, F Tan, Y Chen, Z Wang, H Song… - Neurocomputing, 2023 - Elsevier
The abundance of artificial intelligence AI algorithms and growing computing power has
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …

Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT

Y Wang, A Gupta, FI Tushar, B Riley, A Wang… - Artificial Intelligence in …, 2025 - Elsevier
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index,
which integrates insights from subgroup analysis and personalized AI time-to-event models …

Using bayesian neural networks to select features and compute credible intervals for personalized survival prediction

S Qi, N Kumar, R Verma, JY Xu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
An Individual Survival Distribution (ISD) models a patient's personalized survival probability
at all future time points. Previously, ISD models have been shown to produce accurate and …

A personalized Uncertainty Quantification framework for patient survival models: estimating individual uncertainty of patients with metastatic brain tumors in the …

Y Wang, A Gupta, D Carpenter, T Mullikin… - arxiv preprint arxiv …, 2023 - arxiv.org
TodevelopanovelUncertaintyQuantification (UQ) framework to estimate the uncertainty of
patient survival models in the absence of ground truth, we developed and evaluated our …

[PDF][PDF] Regret minimization with function approximation in extensive-form games

R D'Orazio - 2020 - era.library.ualberta.ca
Computing a Nash equilibrium in zero-sum games, or more generally saddle point
optimization, is a fundamental problem in game theory and machine learning, with …

Solving common-payoff games with approximate policy iteration

S Sokota - 2020 - era.library.ualberta.ca
For artificially intelligent learning systems to be deployed widely in real-world settings, it is
important that they be able to operate decentrally. Unfortunately, decentralized control is …

Individual survival distributions: A more effective tool for survival prediction

HS Haider - 2019 - era.library.ualberta.ca
An accurate model of a patient's individual survival distribution can help determine the
appropriate treatment for terminal patients. Unfortunately, risk scores (eg, from Cox …