AI Medical Compendium Topic:
Bayes Theorem

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A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns.

The American journal of drug and alcohol abuse
Substance use disorder (SUD) is a heterogeneous disorder. Adapting machine learning algorithms to allow for the parsing of intrapersonal and interpersonal heterogeneity in meaningful ways may accelerate the discovery and implementation of clinically...

Optimizing a Deep Residual Neural Network with Genetic Algorithm for Acute Lymphoblastic Leukemia Classification.

Journal of digital imaging
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer worldwide, and it is characterized by the production of immature malignant cells in the bone marrow. Computer vision techniques provide automated analysis that can help specialist...

Predicting Chronic Kidney Disease Using Hybrid Machine Learning Based on Apache Spark.

Computational intelligence and neuroscience
Chronic kidney disease (CKD) has become a widespread disease among people. It is related to various serious risks like cardiovascular disease, heightened risk, and end-stage renal disease, which can be feasibly avoidable by early detection and treatm...

Significance of Visible Non-Invasive Risk Attributes for the Initial Prediction of Heart Disease Using Different Machine Learning Techniques.

Computational intelligence and neuroscience
INTRODUCTION: Heart disease is emerging as the single most critical cause of death worldwide and is one of the costliest chronic conditions.

An Online Weighted Bayesian Fuzzy Clustering Method for Large Medical Data Sets.

Computational intelligence and neuroscience
With the rapid development of artificial intelligence, various medical devices and wearable devices have emerged, enabling people to collect various health data of themselves in hospitals or other places. This has led to a substantial increase in the...

Mental speed is high until age 60 as revealed by analysis of over a million participants.

Nature human behaviour
Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion mo...

Reconstruction of a Fully Paralleled Auditory Spiking Neural Network and FPGA Implementation.

IEEE transactions on biomedical circuits and systems
This paper presents a field-programmable gate array (FPGA) implementation of an auditory system, which is biologically inspired and has the advantages of robustness and anti-noise ability. We propose an FPGA implementation of an eleven-channel hierar...

Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach.

Frontiers in endocrinology
BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies have evaluated the association between multivitamins intake and obesity in children and adolescents.

Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records.

BMC medical informatics and decision making
PURPOSE: Predictively diagnosing infectious diseases helps in providing better treatment and enhances the prevention and control of such diseases. This study uses actual data from a hospital. A multiple infectious disease diagnostic model (MIDDM) is ...

Regional Economic Prediction Model Using Backpropagation Integrated with Bayesian Vector Neural Network in Big Data Analytics.

Computational intelligence and neuroscience
Forecasting economic growth is critical for formulating national economic development policies. Neural Networks are a type of artificial intelligence that may be used to model complex target functions. ANN (Artificial Neural Networks) are one of the ...