AIMC Topic: Models, Statistical

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High-dimensional multiple imputation for partially observed confounders including natural language processing-derived auxiliary covariates.

American journal of epidemiology
Multiple imputation (MI) models can be improved with auxiliary covariates (ACs), but their performance in high-dimensional data remains unclear. We aimed to develop and compare high-dimensional MI (HDMI) methods using structured and natural language ...

Pulling back the curtain: the road from statistical estimand to machine-learning-based estimator for epidemiologists (no wizard required).

American journal of epidemiology
Epidemiologists increasingly use causal inference methods that rely on machine learning, as these approaches can relax unnecessary model specification assumptions. While deriving and studying asymptotic properties of such estimators is a task usually...

Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a machine learning model that can accurately predict the efficacy of HIFU ablation for UFs, assisting t...

A meta-learning method for estimation of causal excursion effects to assess time-varying moderation.

Biometrics
Advances in wearable technologies and health interventions delivered by smartphones have greatly increased the accessibility of mobile health (mHealth) interventions. Micro-randomized trials (MRTs) are designed to assess the effectiveness of the mHea...

Application of machine learning in microwave remediation of total petroleum hydrocarbon contaminated soil: Prediction and key factor identification.

Journal of environmental management
Microwave thermal remediation (TPH) is a promising remediation method for petroleum hydrocarbon contaminated soils due to its high energy efficiency and rapid heating capacity. However, the complexity of influencing factors and their nonlinear intera...

Physics-informed multi-output Gaussian process for dynamical system modeling.

Neural networks : the official journal of the International Neural Network Society
Learning accurate dynamics models is crucial for model-based reinforcement learning. Gaussian processes (GPs), as a probabilistic modeling approach, have been widely used for dynamical system modeling. However, standard GPs are designed for single-ou...

Accelerating Diffusion: Task-Optimized latent diffusion models for rapid CT denoising.

Computers in biology and medicine
Computed tomography (CT) systems are indispensable for diagnostics but pose risks due to radiation exposure. Low-dose CT (LDCT) mitigates these risks but introduces noise and artifacts that compromise diagnostic accuracy. While deep learning methods,...

A comprehensive review of ICU readmission prediction models: From statistical methods to deep learning approaches.

Artificial intelligence in medicine
The prediction of Intensive Care Unit (ICU) readmission has become a crucial area of research due to the increasing demand for ICU resources and the need to provide timely interventions to critically ill patients. In recent years, several studies hav...

Spatio-temporal crash severity analysis with cost-sensitive multi-graphs attention network.

Accident; analysis and prevention
Most conventional crash severity models attempt to achieve a low classification error rate, implicitly assuming the same losses for all classification errors. In this paper, we suggest that this setting has limitations in terms of reasonableness, as ...

Probabilistic memory auto-encoding network for abnormal behavior detection in surveillance video.

Neural networks : the official journal of the International Neural Network Society
Abnormal behavior detection in surveillance video, as one of the essential functions in the intelligent surveillance system, plays a vital role in anti-terrorism, maintaining stability, and ensuring social security. Aiming at the problem of extremely...