AIMC Topic: Algorithms

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CyGate Provides a Robust Solution for Automatic Gating of Single Cell Cytometry Data.

Analytical chemistry
To gain a better understanding of the complex human immune system, it is necessary to measure and interpret numerous cellular protein expressions at the single cell level. Mass cytometry is a relatively new technology that offers unprecedented inform...

The Impact of Data on Structure-Based Binding Affinity Predictions Using Deep Neural Networks.

International journal of molecular sciences
Artificial intelligence (AI) has gained significant traction in the field of drug discovery, with deep learning (DL) algorithms playing a crucial role in predicting protein-ligand binding affinities. Despite advancements in neural network architectur...

Efficient automated error detection in medical data using deep-learning and label-clustering.

Scientific reports
Medical datasets inherently contain errors from subjective or inaccurate test results, or from confounding biological complexities. It is difficult for medical experts to detect these elusive errors manually, due to lack of contextual information, li...

Machine learning prediction model based on enhanced bat algorithm and support vector machine for slow employment prediction.

PloS one
The employment of college students is an important issue that affects national development and social stability. In recent years, the increase in the number of graduates, the pressure of employment, and the epidemic have made the phenomenon of 'slow ...

Classification of brain tumours from MRI images using deep learning-enabled hybrid optimization algorithm.

Network (Bristol, England)
Brain tumours are produced by the uncontrolled, and unusual tissue growth of brain. Because of the wide range of brain tumour locations, potential shapes, and image intensities, segmentation of the brain tumour by magnetic resonance imaging (MRI) is ...

MDSR-NMF: Multiple deconstruction single reconstruction deep neural network model for non-negative matrix factorization.

Network (Bristol, England)
Dimension reduction is one of the most sought-after strategies to cope with high-dimensional ever-expanding datasets. To address this, a novel deep-learning architecture has been designed with multiple deconstruction and single reconstruction layers ...

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava.

The plant genome
This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, a...

Hybrid optimization assisted channel selection of EEG for deep learning model-based classification of motor imagery task.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: To design and develop an approach named HC + SMA-SSA scheme for classifying motor imagery task.

Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol.