AIMC Topic: Algorithms

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Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.

European radiology
OBJECTIVES: To benchmark the performance of a calibrated 3D convolutional neural network (CNN) applied to multiparametric MRI (mpMRI) for risk assessment of clinically significant prostate cancer (csPCa) using decision curve analysis (DCA).

Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning.

International journal of computer assisted radiology and surgery
PURPOSE: Inexpensive benchtop training systems offer significant advantages to meet the increasing demand of training surgeons and gastroenterologists in flexible endoscopy. Established scoring systems exist, based on task duration and mistake evalua...

Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells.

International journal of environmental research and public health
The emergence of new technologies to incorporate and analyze data with high-performance computing has expanded our capability to accurately predict any incident. Supervised Machine learning (ML) can be utilized for a fast and consistent prediction, a...

Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Sensors (Basel, Switzerland)
Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brain diseases. However, major depressive disorder may also cause temporary deterioration of one's cognition known as pseudodementia. Differentiating a tr...

Investigating the challenges and generalizability of deep learning brain conductivity mapping.

Physics in medicine and biology
To investigate deep learning electrical properties tomography (EPT) for application on different simulated and in-vivo datasets, including pathologies for brain conductivity reconstructions, 3D patch-based convolutional neural networks were trained t...

New machine learning method for image-based diagnosis of COVID-19.

PloS one
COVID-19 is a worldwide epidemic, as announced by the World Health Organization (WHO) in March 2020. Machine learning (ML) methods can play vital roles in identifying COVID-19 patients by visually analyzing their chest x-ray images. In this paper, a ...

Development of neural fractional order PID controller with emulator.

ISA transactions
This paper focuses on tuning parameters of fractional order PID controller (FOPID) by using neural networks (NNs). For tuning the coefficients of the controller and orders of fractional derivative and integrator, five exclusive NNs are employed. More...

Amur tiger stripes: individual identification based on deep convolutional neural network.

Integrative zoology
The automatic individual identification of Amur tigers (Panthera tigris altaica) is important for population monitoring and making effective conservation strategies. Most existing research primarily relies on manual identification, which does not sca...

Predicting protein subcellular location with network embedding and enrichment features.

Biochimica et biophysica acta. Proteins and proteomics
The subcellular location of a protein is highly related to its function. Identifying the location of a given protein is an essential step for investigating its related problems. Traditional experimental methods can produce solid determination. Howeve...