AI Medical Compendium Topic

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Bioinspired Soft Microrobots with Precise Magneto-Collective Control for Microvascular Thrombolysis.

Advanced materials (Deerfield Beach, Fla.)
New-era soft microrobots for biomedical applications need to mimic the essential structures and collective functions of creatures from nature. Biocompatible interfaces, intelligent functionalities, and precise locomotion control in a collective manne...

In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

International journal of molecular sciences
The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quant...

AxoNet: A deep learning-based tool to count retinal ganglion cell axons.

Scientific reports
In this work, we develop a robust, extensible tool to automatically and accurately count retinal ganglion cell axons in optic nerve (ON) tissue images from various animal models of glaucoma. We adapted deep learning to regress pixelwise axon count de...

Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage.

Analytica chimica acta
All living systems are maintained by a constant flux of metabolic energy and, among the different reactions, the process of lipids storage and lipolysis is of fundamental importance. Current research has focused on the investigation of lipid droplets...

On the boundary conditions of avoidance memory reconsolidation: An attractor network perspective.

Neural networks : the official journal of the International Neural Network Society
The reconsolidation and extinction of aversive memories and their boundary conditions have been extensively studied. Knowing their network mechanisms may lead to the development of better strategies for the treatment of fear and anxiety-related disor...

From spatial navigation via visual construction to episodic memory and imagination.

Biological cybernetics
This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affo...

In Silico Prediction of Metabolic Epoxidation for Drug-like Molecules via Machine Learning Methods.

Molecular informatics
Epoxidation is one of the reactions in drug metabolism. Since epoxide metabolites would bind with proteins or DNA covalently, drugs should avoid epoxidation metabolism in the body. Due to the instability of epoxide, it is difficult to determine epoxi...

Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap-Deep Learning.

Molecules (Basel, Switzerland)
The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that senses environmental exogenous and endogenous ligands or xenobiotic chemicals. In particular, exposure of the liver to environmental metabolism-disrupting chemicals c...

Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain.

Magnetic resonance in medicine
PURPOSE: The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy ( H-MRS).