AIMC Topic: Bayes Theorem

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Predicting skilled delivery service use in Ethiopia: dual application of logistic regression and machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Skilled assistance during childbirth is essential to reduce maternal deaths. However, in Ethiopia, which is among the six countries contributing to more than half of the global maternal deaths, the coverage of births attended by skilled h...

Breast Cancer Identification via Thermography Image Segmentation with a Gradient Vector Flow and a Convolutional Neural Network.

Journal of healthcare engineering
Breast cancer is the most common cancer among women worldwide with about half a million cases reported each year. Mammary thermography can offer early diagnosis at low cost if adequate thermographic images of the breasts are taken. The identification...

Estimating treatment effects with machine learning.

Health services research
OBJECTIVE: To demonstrate the performance of methodologies that include machine learning (ML) algorithms to estimate average treatment effects under the assumption of exogeneity (selection on observables).

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Scientific reports
Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely a...

Utilizing Machine Learning for Efficient Parameterization of Coarse Grained Molecular Force Fields.

Journal of chemical information and modeling
We present a machine learning approach to automated force field development in dissipative particle dynamics (DPD). The approach employs Bayesian optimization to parametrize a DPD force field against experimentally determined partition coefficients. ...

Enhancing the security of patients' portals and websites by detecting malicious web crawlers using machine learning techniques.

International journal of medical informatics
INTRODUCTION: There is increasing demand for access to medical information via patients' portals. However, one of the challenges towards widespread utilisation of such service is maintaining the security of those portals. Recent reports show an alarm...

EEG-based single-channel authentication systems with optimum electrode placement for different mental activities.

Biomedical journal
BACKGROUND: Electroencephalogram (EEG) signals of a brain contain a unique pattern for each person and the potential for biometric applications. Authentication and security is a very important issue in our life and brainwave-based authentication is a...

A superpixel-driven deep learning approach for the analysis of dermatological wounds.

Computer methods and programs in biomedicine
BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi...

Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling.

IEEE transactions on medical imaging
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...