AIMC Topic: Machine Learning

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Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review.

Sensors (Basel, Switzerland)
An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the si...

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification.

Physics in medicine and biology
In the artificial intelligence era, machine learning (ML) techniques have gained more and more importance in the advanced analysis of medical images in several fields of modern medicine. Radiomics extracts a huge number of medical imaging features re...

Identification of Cardiac Patients Based on the Medical Conditions Using Machine Learning Models.

Computational intelligence and neuroscience
Chronic diseases are the most severe health concern today, and heart disease is one of them. Coronary artery disease (CAD) affects blood flow to the heart, and it is the most common type of heart disease which causes a heart attack. High blood pressu...

Sentiment Analysis of Animated Film Reviews Using Intelligent Machine Learning.

Computational intelligence and neuroscience
Film is an essential expression of a country's cultural soft power in terms of cross-cultural exchange. In addition, film is also the most direct and favourable means of communication. Along with the expansion and development of the Chinese film mark...

AIOps Architecture in Data Center Site Infrastructure Monitoring.

Computational intelligence and neuroscience
AIOps (artificial intelligence for IT operations) has been growing rapidly in recent years. However, it can be seen that the vast majority of AIOps applications are implemented in the IT domain. In contrast, there are few applications in the data cen...

A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field.

BioMed research international
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the facto...

Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth.

Human brain mapping
Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age i...

Traceable machine learning real-time quality control based on patient data.

Clinical chemistry and laboratory medicine
OBJECTIVES: Patient-based real-time quality control (PBRTQC) has gained attention as an alternative/integrative tool for internal quality control (iQC). However, it is still doubted for its performance and its application in real clinical settings. W...

Simplified Transfer Learning for Chest Radiography Models Using Less Data.

Radiology
Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations can be further exacerbated by distribution shifts, such as rapid changes in patient populations and s...

An automatic method to quantify trichomes in Arabidopsis thaliana.

Plant science : an international journal of experimental plant biology
Trichomes are unicellular or multicellular hair-like appendages developed on the aerial plant epidermis of most plant species that act as a protective barrier against natural hazards. For this reason, evaluating the density of trichomes is a valuable...