AI Medical Compendium Topic

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Statistical models versus machine learning approach for competing risks in proctological surgery.

Updates in surgery
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for pr...

Sexual dimorphism of the humerus bones in a French sample: comparison of several statistical models including machine learning models.

International journal of legal medicine
Sex estimation is an important part of skeletal analysis and forensic identification. Traditionally pelvic traits are utilized for accurate sex estimation. However, the long bones, especially humerus, have been proved to be as effective for determine...

Multicategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.

Statistical methods in medical research
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most...

An examination of daily CO emissions prediction through a comparative analysis of machine learning, deep learning, and statistical models.

Environmental science and pollution research international
Human-induced global warming, primarily attributed to the rise in atmospheric CO, poses a substantial risk to the survival of humanity. While most research focuses on predicting annual CO emissions, which are crucial for setting long-term emission mi...

Survival parametric modeling for patients with heart failure based on Kernel learning.

BMC medical research methodology
Time-to-event data are very common in medical applications. Regression models have been developed on such data especially in the field of survival analysis. Kernels are used to handle even more complicated and enormous quantities of medical data by i...

Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies.

Computer methods and programs in biomedicine
The rise in minimally invasive procedures has created a demand for efficient and reliable planning software to predict intra- and post-operative outcomes. Surrogate modelling has shown promise, but challenges remain, particularly in cardiovascular ap...

Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.

Accident; analysis and prevention
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technolo...

The Harms of Class Imbalance Corrections for Machine Learning Based Prediction Models: A Simulation Study.

Statistics in medicine
INTRODUCTION: Risk prediction models are increasingly used in healthcare to aid in clinical decision-making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk estimates) is critical. Data available for model develo...

From statistics to deep learning: Using large language models in psychiatric research.

International journal of methods in psychiatric research
BACKGROUND: Large Language Models (LLMs) hold promise in enhancing psychiatric research efficiency. However, concerns related to bias, computational demands, data privacy, and the reliability of LLM-generated content pose challenges. GAP: Existing st...