AIMC Topic: Algorithms

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Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

BioMed research international
BACKGROUND: The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medi...

Weakly-supervised learning for lung carcinoma classification using deep learning.

Scientific reports
Lung cancer is one of the major causes of cancer-related deaths in many countries around the world, and its histopathological diagnosis is crucial for deciding on optimum treatment strategies. Recently, Artificial Intelligence (AI) deep learning mode...

The use of machine learning in rare diseases: a scoping review.

Orphanet journal of rare diseases
BACKGROUND: Emerging machine learning technologies are beginning to transform medicine and healthcare and could also improve the diagnosis and treatment of rare diseases. Currently, there are no systematic reviews that investigate, from a general per...

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Risk analysis : an official publication of the Society for Risk Analysis
Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the ...

Comparing Machine Learning Algorithms for Predicting Drug-Induced Liver Injury (DILI).

Molecular pharmaceutics
Drug-induced liver injury (DILI) is one the most unpredictable adverse reactions to xenobiotics in humans and the leading cause of postmarketing withdrawals of approved drugs. To date, these drugs have been collated by the FDA to form the DILIRank da...

Utilization of a Deep Learning Algorithm for Microscope-Based Fatty Vacuole Quantification in a Fatty Liver Model in Mice.

Toxicologic pathology
Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vessels and bile ducts, is an example where the traditional semiquantitative pathology assessment can be enhanced with artificial intelligence (AI) algorit...

CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. It has so far infected around 1.8 million people and claimed approximately 114,698 lives overall. As...

Batch process fault detection for multi-stage broad learning system.

Neural networks : the official journal of the International Neural Network Society
In the real industrial production process, some minor faults are difficult to be detected by multivariate statistical analysis methods with mean and variance as detection indicators due to the aging equipment and catalyst deactivation. With structura...