AIMC Topic: Machine Learning

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Enhancing classification of cells procured from bone marrow aspirate smears using generative adversarial networks and sequential convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Leukemia represents 30% of all pediatric cancers and is considered the most common malignancy affecting adults and children. Cell differential count obtained from bone marrow aspirate smears is crucial for diagnosing hematol...

Comparison of the performances of machine learning and deep learning in improving the quality of low dose lung cancer PET images.

Japanese journal of radiology
PURPOSE: To compare the performances of machine learning (ML) and deep learning (DL) in improving the quality of low dose (LD) lung cancer PET images and the minimum counts required.

Age group prediction with panoramic radiomorphometric parameters using machine learning algorithms.

Scientific reports
The aim of this study is to investigate the relationship of 18 radiomorphometric parameters of panoramic radiographs based on age, and to estimate the age group of people with permanent dentition in a non-invasive, comprehensive, and accurate manner ...

An Efficient Machine Learning-Based Feature Optimization Model for the Detection of Dyslexia.

Computational intelligence and neuroscience
Dyslexia is among the most common neurological disorders in children. Detection of dyslexia therefore remains an important pursuit for the research works across various domains which is illustrated by the plethora of work presented in diverse scienti...

A Novel Piano Arrangement Timbre Intelligent Recognition System Using Multilabel Classification Technology and KNN Algorithm.

Computational intelligence and neuroscience
In this paper, melody and harmony are regarded as the task of machine learning, and a piano arranger timbre recognition system based on AI (Artificial Intelligence) is constructed by training a series of samples. The short-time Fourier transform spec...

Realization of English Instructional Resources Clusters Reconstruction System Using the Machine Learning Model.

Computational intelligence and neuroscience
Based on ML algorithm, this paper puts forward a method that can search instructional resources through keyword indexing technology, and then cluster and recombine the related results and present them centrally. In this paper, the semantic processing...

A Machine Learning Approach to Identify Previously Unconsidered Causes for Complications in Aesthetic Breast Augmentation.

Aesthetic plastic surgery
INTRODUCTION: Primary breast augmentation is one of the most commonly requested aesthetic procedures. Considering the large number of procedures performed in connection with a high demand, it is crucial to prevent complications. For this reason, find...

Towards automated coronary artery segmentation: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Vessel segmentation is the first processing stage of 3D medical images for both clinical and research use. Current segmentation methods are tedious and time consuming, requiring significant manual correction and hence are in...

Application of deep learning methods: From molecular modelling to patient classification.

Experimental cell research
We are now well into the information driven age with complex, heterogeneous, datasets in the biological sciences continuing to grow at a rapid pace. Moreover, distilling of such datasets, to find new governing principles, are underway. Leading the su...

Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized b...