AI Medical Compendium Topic

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

Rats

Showing 21 to 30 of 578 articles

Clear Filters

Recapitulating the electrophysiological features of in vivo biological networks by using a real-time hardware Spiking Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroceutical methodologies utilized for treating neurological disorders, including stroke, can leverage neuromorphic engineering principles to design devices capable of seamlessly interfacing with the neural system. This paper introduces a bank of...

Robot-Assisted Stereotactic Microinjection Method for Precision Cell Transplantation in Rat and Canine Models.

Cell transplantation
Cell transplantation is a promising approach for addressing neurodegenerative conditions. In this study, we developed a robot-assisted stereotactic microinjection system for transplanting cells. We evaluated the factors that affect cellular graft via...

Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

International journal of medical sciences
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...

Prediction and validation of anoikis-related genes in neuropathic pain using machine learning.

PloS one
BACKGROUND: Neuropathic pain (NP) can be induced by a variety of clinical conditions, such as spinal cord injury, lumbar disc herniation (LDH), lumbar spinal stenosis, diabetes, herpes zoster, and spinal cord tumors, and inflammatory stimuli. The pat...

A deep learning strategy to identify cell types across species from high-density extracellular recordings.

Cell
High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but fail to reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals an...

Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Scientific reports
Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged scanning periods, which may impose moving artifacts and affect the promptness of diagnosis and treatment of time-sensitive diseases like stroke. This st...

Predicting Pharmacokinetics in Rats Using Machine Learning: A Comparative Study Between Empirical, Compartmental, and PBPK-Based Approaches.

Clinical and translational science
A successful drug needs to combine several properties including high potency and good pharmacokinetic (PK) properties to sustain efficacious plasma concentration over time. To estimate required doses for preclinical animal efficacy models or for the ...

A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure.

Ecotoxicology and environmental safety
BACKGROUND: Within the past two decades, high-profile cases of melamine (MA) exposure have raised significant toxicological concerns, particularly regarding food adulteration. While widely used as a fundamental organic chemical intermediate in variou...

Multitarget Natural Compounds for Ischemic Stroke Treatment: Integration of Deep Learning Prediction and Experimental Validation.

Journal of chemical information and modeling
Ischemic stroke's complex pathophysiology demands therapeutic approaches targeting multiple pathways simultaneously, yet current treatments remain limited. We developed an innovative drug discovery pipeline combining a deep learning approach with exp...

Of rats and robots: A mutual learning paradigm.

Journal of the experimental analysis of behavior
Robots are increasingly used alongside Skinner boxes to train animals in operant conditioning tasks. Similarly, animals are being employed in artificial intelligence research to train various algorithms. However, both types of experiments rely on uni...