AI Medical Compendium Topic

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

Rats

Showing 241 to 250 of 578 articles

Clear Filters

Automatic rat brain image segmentation using triple cascaded convolutional neural networks in a clinical PET/MR.

Physics in medicine and biology
The purpose of this work was to develop and evaluate a deep learning approach for automatic rat brain image segmentation of magnetic resonance imaging (MRI) images in a clinical PET/MR, providing a useful tool for analyzing studies of the pathology a...

Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning.

Journal of pharmaceutical sciences
Research into pharmacokinetics plays an important role in the development process of new drugs. Accurately predicting human pharmacokinetic parameters from preclinical data can increase the success rate of clinical trials. Since clearance (CL) which ...

A stack LSTM structure for decoding continuous force from local field potential signal of primary motor cortex (M1).

BMC bioinformatics
BACKGROUND: Brain Computer Interfaces (BCIs) translate the activity of the nervous system to a control signal which is interpretable for an external device. Using continuous motor BCIs, the user will be able to control a robotic arm or a disabled lim...

Application of Machine-Learning Methods to Recognize mitoBK Channels from Different Cell Types Based on the Experimental Patch-Clamp Results.

International journal of molecular sciences
(1) Background: In this work, we focus on the activity of large-conductance voltage- and Ca2+-activated potassium channels (BK) from the inner mitochondrial membrane (mitoBK). The characteristic electrophysiological features of the mitoBK channels ar...

Use of Machine Learning to Re-Assess Patterns of Multivariate Functional Recovery after Fluid Percussion Injury: Operation Brain Trauma Therapy.

Journal of neurotrauma
Traumatic brain injury (TBI) is a leading cause of death and disability. Yet, despite immense research efforts, treatment options remain elusive. Translational failures in TBI are often attributed to the heterogeneity of the TBI population and limite...

An efficient method for building a database of diatom populations for drowning site inference using a deep learning algorithm.

International journal of legal medicine
Seasonal or monthly databases of the diatom populations in specific bodies of water are needed to infer the drowning site of a drowned body. However, existing diatom testing methods are laborious, time-consuming, and costly and usually require specif...

Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy.

Toxicologic pathology
Quantification of retinal atrophy, caused by therapeutics and/or light, by manual measurement of retinal layers is labor intensive and time-consuming. In this study, we explored the role of deep learning (DL) in automating the assessment of retinal a...

Bacterial endosymbiont inhabiting leaves and their antioxidant and antidiabetic potential.

Journal of complementary & integrative medicine
OBJECTIVES: Research on endosymbionts is emerging globally and is considered as a potential source of bioactive phytochemicals. The present study examines the antioxidant and antidiabetic of the endophytic crude extract isolated from leaves.

Using Artificial Intelligence to Detect, Classify, and Objectively Score Severity of Rodent Cardiomyopathy.

Toxicologic pathology
Rodent progressive cardiomyopathy (PCM) encompasses a constellation of microscopic findings commonly seen as a spontaneous background change in rat and mouse hearts. Primary histologic features of PCM include varying degrees of cardiomyocyte degenera...

A Workflow for the Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks.

Toxicologic pathology
In order to automate the counting of ovarian follicles required in multigeneration reproductive studies performed in the rat according to Organization for Economic Co-operation and Development guidelines 443 and 416, the application of deep neural ne...