AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cell Size

Showing 1 to 10 of 14 articles

Clear Filters

Boi-Ogi-To, a Traditional Japanese Kampo Medicine, Promotes Cellular Excretion of Chloride and Water by Activating Volume-Sensitive Outwardly Rectifying Anion Channels.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
The Japanese Kampo medicine Boi-ogi-to (BOT) is known as an effective therapeutic agent for edema and nephrosis by promoting the excretion of excess body fluids. Despite its empirical effectiveness, scientific evidence supporting its effectiveness re...

Intelligent image-based deformation-assisted cell sorting with molecular specificity.

Nature methods
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on...

CTRL - a label-free artificial intelligence method for dynamic measurement of single-cell volume.

Journal of cell science
Measuring the physical size of a cell is valuable in understanding cell growth control. Current single-cell volume measurement methods for mammalian cells are labor intensive, inflexible and can cause cell damage. We introduce CTRL: Cell Topography R...

An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension.

Sensors (Basel, Switzerland)
Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still ...

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

PLoS computational biology
Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated diseases. Using a large study (n = 1,288) from 4 independent cohorts, we aimed to investigate the re...

Cell morphology-based machine learning models for human cell state classification.

NPJ systems biology and applications
Herein, we implement and access machine learning architectures to ascertain models that differentiate healthy from apoptotic cells using exclusively forward (FSC) and side (SSC) scatter flow cytometry information. To generate training data, colorecta...

Detecting cells rotations for increasing the robustness of cell sizing by impedance measurements, with or without machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The Coulter principle is a widespread technique for sizing red blood cells (RBCs) in hematological analyzers. It is based on the monitoring of the electrical perturbations generated by cells passing through a micro-orifice, in which a concentrated el...

A deep learning approach for automation in neurite tracing and cell size estimation from differential contrast images under healthy and hypoxic condition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Chronic hypoxia is known to be a major cause of neurite length retraction followed be degeneration. Specifically, laser scanning confocal microscopy (LSCM) based-contrast imaging is used for monitoring neuronal morphology under hypoxic condition. Alt...

Using optimal transport theory to optimize a deep convolutional neural network microscopic cell counting method.

Medical & biological engineering & computing
Medical image processing has become increasingly important in recent years, particularly in the field of microscopic cell imaging. However, accurately counting the number of cells in an image can be a challenging task due to the significant variation...

Towards Fluorescent-Tag-Less Viral Titration: Automated Estimation of Cell-Size Distribution and Infection Level from Phase-Contrast Microscopy Using Deep Learning and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated detection of infected insect cells is one of the crucial tasks in the field of recombinant protein production and vaccine development. The major challenge lies in manual segmentation of cells and quantifying cell size distribution is tediou...