AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Bayes Theorem

Showing 511 to 520 of 1712 articles

Clear Filters

Human monkeypox diagnose (HMD) strategy based on data mining and artificial intelligence techniques.

Computers in biology and medicine
In May 2022, monkeypox re-emerged as a rare zoonotic disease that is an important viral disease for public health. Monkeypox can be transmitted from animals to humans, between humans through close contact with an infected human, or with a virus stain...

Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series.

International journal of environmental research and public health
Tree-based machine learning methods have gained traction in the statistical and data science fields. They have been shown to provide better solutions to various research questions than traditional analysis approaches. To encourage the uptake of tree-...

Evaluation of Machine Learning Techniques for Traffic Flow-Based Intrusion Detection.

Sensors (Basel, Switzerland)
Cybersecurity is one of the great challenges of today's world. Rapid technological development has allowed society to prosper and improve the quality of life and the world is more dependent on new technologies. Managing security risks quickly and eff...

Machine Learning-Based Ensemble Classifiers for Anomaly Handling in Smart Home Energy Consumption Data.

Sensors (Basel, Switzerland)
Addressing data anomalies (e.g., garbage data, outliers, redundant data, and missing data) plays a vital role in performing accurate analytics (billing, forecasting, load profiling, etc.) on smart homes' energy consumption data. From the literature, ...

Fault Early Warning Model for High-Speed Railway Train Based on Feature Contribution and Causal Inference.

Sensors (Basel, Switzerland)
The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black box model is difficult to interpret, making it impossible for this technology to ...

Application of deep learning models for detection of subdural hematoma: a systematic review and meta-analysis.

Journal of neurointerventional surgery
BACKGROUND: This study aimed to investigate the application of deep learning (DL) models for the detection of subdural hematoma (SDH).

Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature.

Journal of nursing management
AIM: The aim of this review is to examine the effectiveness of artificial intelligence in predicting multimorbid diabetes-related complications.

Sparse Bayesian Learning Based on Collaborative Neurodynamic Optimization.

IEEE transactions on cybernetics
Regression in a sparse Bayesian learning (SBL) framework is usually formulated as a global optimization problem with a nonconvex objective function and solved in a majorization-minimization framework where the solution quality and consistency depend ...

Uncertainty-aware self-supervised neural network for livermapping with relaxation constraint.

Physics in medicine and biology
.T1ρmapping is a promising quantitative MRI technique for the non-invasive assessment of tissue properties. Learning-based approaches can mapT1ρfrom a reduced number ofT1ρweighted images but requires significant amounts of high-quality training data....