AI Medical Compendium Topic:
Bayes Theorem

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Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models.

Diabetes research and clinical practice
AIMS: This study aims to predict poor glycemic control during Ramadan among non-fasting patients with diabetes using machine learning models.

A Two-Stage Feature Point Detection and Marking Approach Based on the Labeled Multi-Bernoulli Filter.

Sensors (Basel, Switzerland)
In recent years, various algorithms using random finite sets (RFS) to solve the issue of simultaneous localization and mapping (SLAM) have been proposed. Compared with the traditional method, the advantage of the RFS method is that it can avoid data ...

Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.

Nature communications
Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the dynamics of epidemics. Standard methods, including maximum-likelihood and Bayesian approaches, gene...

Mediation analysis using Bayesian tree ensembles.

Psychological methods
We present a general framework for causal mediation analysis using nonparametric Bayesian methods in the potential outcomes framework. Our model, which we refer to as the Bayesian causal mediation forests model, combines recent advances in Bayesian m...

A Drug Recommendation Model Based on Message Propagation and DDI Gating Mechanism.

IEEE journal of biomedical and health informatics
Drug recommendation task based on the deep learning model has been widely studied and applied in the health care field in recent years. However, the accuracy of drug recommendation models still needs to be improved. In addition, the existing recommen...

Comparison of machine learning classification techniques to predict implantation success in an IVF treatment cycle.

Reproductive biomedicine online
RESEARCH QUESTION: Which machine learning model predicts the implantation outcome better in an IVF cycle? What is the importance of each variable in predicting the implantation outcome in an IVF cycle?

Aglow: A Fluorescence Assay and Machine Learning Model to Identify Inhibitors of Intracellular Infection.

ACS infectious diseases
is a genus of Gram-negative bacteria that has for centuries caused large-scale morbidity and mortality. In recent years, the resurgence of rickettsial diseases as a major cause of pyrexias of unknown origin, bioterrorism concerns, vector movement, a...

Rational Design of Field-Effect Sensors Using Partial Differential Equations, Bayesian Inversion, and Artificial Neural Networks.

Sensors (Basel, Switzerland)
Silicon nanowire field-effect transistors are promising devices used to detect minute amounts of different biological species. We introduce the theoretical and computational aspects of forward and backward modeling of biosensitive sensors. Firstly, w...

Bayesian statistics-guided label refurbishment mechanism: Mitigating label noise in medical image classification.

Medical physics
PURPOSE: Deep neural networks (DNNs) have been widely applied in medical image classification, benefiting from its powerful mapping capability among medical images. However, these existing deep learning-based methods depend on an enormous amount of c...

Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power.

Proceedings of the National Academy of Sciences of the United States of America
Large-scale measurements linking genetic background to biological function have driven a need for models that can incorporate these data for reliable predictions and insight into the underlying biophysical system. Recent modeling efforts, however, pr...