AI Medical Compendium Topic

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

Disease Models, Animal

Showing 51 to 60 of 274 articles

Clear Filters

Application of Machine Learning in a Rodent Malaria Model for Rapid, Accurate, and Consistent Parasite Counts.

The American journal of tropical medicine and hygiene
Rodent malaria models serve as important preclinical antimalarial and vaccine testing tools. Evaluating treatment outcomes in these models often requires manually counting parasite-infected red blood cells (iRBCs), a time-consuming process, which can...

Severe degranulation of mesenteric mast cells in an experimental rat mammary tumor model.

Turkish journal of medical sciences
BACKGROUND/AIM: Breast cancers are one of the most common cancers in women and are responsible for many deaths worldwide. Mast cells are inflammatory cells. Their role in cancers is controversial, and there is limited data on systemic mast cell activ...

An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Microbes are extensively present among various cancer tissues and play critical roles in carcinogenesis and treatment responses. However, the underlying relationships between intratumoral microbes and tumors remain poorly understood. Here, a MIcrobia...

Advanced rehabilitation in ischaemic stroke research.

Stroke and vascular neurology
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physic...

Dynamic changes in pyroptosis following spinal cord injury and the identification of crucial molecular signatures through machine learning and single-cell sequencing.

Journal of pharmaceutical and biomedical analysis
The pathological cascade of spinal cord injury (SCI) is highly intricate. The onset of neuroinflammation can exacerbate the extent of damage. Pyroptosis is a form of inflammation-linked programmed cell death (PCD), the inhibition of pyroptosis can pa...

Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model.

Lipids in health and disease
BACKGROUND: Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till ...

Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept.

Journal of clinical monitoring and computing
Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of...

Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

BMC medical imaging
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predict...

Mechanisms of QingRe HuoXue Formula in atherosclerosis Treatment: An integrated approach using Bioinformatics, Machine Learning, and experimental validation.

International immunopharmacology
BACKGROUND: Atherosclerosis (AS) is the main cause of coronary heart disease, cerebral infarction, and peripheral vascular disease. QingRe HuoXue Formula (QRHXF), a common prescription of traditional Chinese medicine, has a definite effect on the cli...

Development of artificial intelligence-driven biosignal-sensitive cardiopulmonary resuscitation robot.

Resuscitation
AIM OF THE STUDY: We evaluated whether an artificial intelligence (AI)-driven robot cardiopulmonary resuscitation (CPR) could improve hemodynamic parameters and clinical outcomes.