AIMC Topic: Bayes Theorem

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Policy search in continuous action domains: An overview.

Neural networks : the official journal of the International Neural Network Society
Continuous action policy search is currently the focus of intensive research, driven both by the recent success of deep reinforcement learning algorithms and the emergence of competitors based on evolutionary algorithms. In this paper, we present a b...

A stochastic variational framework for Recurrent Gaussian Processes models.

Neural networks : the official journal of the International Neural Network Society
Gaussian Processes (GPs) models have been successfully applied to the problem of learning from sequential observations. In such context, the family of Recurrent Gaussian Processes (RGPs) have been recently introduced with a specifically designed stru...

A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a fully developed computer aided diagnosis (CAD) system for early knee OsteoArthritis (OA) detection using knee X-ray imaging and machine learning algorithms. The X-ray images are first preprocessed in the Fourier domain using a c...

Detection of Extraprostatic Extension of Cancer on Biparametric MRI Combining Texture Analysis and Machine Learning: Preliminary Results.

Academic radiology
RATIONALE AND OBJECTIVES: Extraprostatic extension of disease (EPE) has a major role in risk stratification of prostate cancer patients. Currently, pretreatment local staging is performed with MRI, while the gold standard is represented by histopatho...

The influence of maternal agency on severe child undernutrition in conflict-ridden Nigeria: Modeling heterogeneous treatment effects with machine learning.

PloS one
Nigeria is one of the fastest growing African economies, yet struggles with armed conflict, poverty, and morbidity. An area of high concern is how this situation affects vulnerable families and their children. A key pathway in improving the situation...

Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

The Journal of arthroplasty
BACKGROUND: Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objec...

The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining.

International journal of medical informatics
BACKGROUND: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the disease. It is believed that new data analysis methods may be applied to this disease, and this may be...

Private naive bayes classification of personal biomedical data: Application in cancer data analysis.

Computers in biology and medicine
Clinicians would benefit from access to predictive models for diagnosis, such as classification of tumors as malignant or benign, without compromising patients' privacy. In addition, the medical institutions and companies who own these medical inform...

An extensive experimental survey of regression methods.

Neural networks : the official journal of the International Neural Network Society
Regression is a very relevant problem in machine learning, with many different available approaches. The current work presents a comparison of a large collection composed by 77 popular regression models which belong to 19 families: linear and general...

Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning.

IEEE transactions on neural networks and learning systems
Neural decoding, which aims to predict external visual stimuli information from evoked brain activities, plays an important role in understanding human visual system. Many existing methods are based on linear models, and most of them only focus on ei...