Artificial Intelligence Medical Compendium

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

Showing 24,211 to 24,220 of 217,425 articles

Thermal and solutal analysis of oxytactic microbes in bioconvection slip flow of trihybrid nanofluid with activation energy using artificial neural network.

Discover nano
In this work, the intelligent Levenberg-Marquardt optimization approach is applied to evaluate the activation energy influence on thermo-bioconvection flow of a trihybrid nanofluid including oxytactic microbes via a plate using integrated numerical c... read more 

Identification of tolerogenic dendritic cells-related prognostic biomarkers in Wilms tumor via machine learning integration.

Discover oncology
Wilms tumor (WT) is the most common pediatric kidney cancer. Tolerogenic dendritic cells (TolDCs) promote tumor immune evasion in the tumor microenvironment. Therefore, establishing a TolDC-based prognostic model for WT holds significant clinical val... read more 

Warning people about the risk of AI error mitigates human acquisition of AI bias.

Cognitive research: principles and implications
Empirical evidence has demonstrated the power of AI to influence human decisions and the risk of humans acquiring AI biases. Therefore, there is a clear need to develop strategies to mitigate such threat. In three experiments, set in a medical contex... read more 

Predicting Postoperative Anterior Chamber Depth, Intraocular Lens Tilt, and Decentration Using an Internally Validated Machine Learning Model.

Ophthalmology and therapy
INTRODUCTION: Precise intraocular lens (IOL) positioning is critical for optimal visual outcomes in cataract surgery, particularly with advanced IOLs. Misalignment can lead to refractive errors, astigmatism, and higher-order aberrations. This study a... read more 

Neural Stem Cell-Derived Extracellular Vesicles: The Next Frontier in Neurological and Neurodegenerative Diseases.

Stem cell reviews and reports
The present manuscript provides a comprehensive overview of neural stem cell (NSC)-derived extracellular vesicles (NSC-EVs( as a cell-free approach to treating central nervous system (CNS) disorders. The study noted that NSCs are regenerative and neu... read more 

Identifying diagnostic biomarkers in functional motor disorders through multimodal behavioral, neurophysiological, and imaging assessment using explainable machine learning.

Journal of neurology
BACKGROUND: Functional motor disorders (FMDs) represent a frequent and disabling neurological condition. The lack of reliable diagnostic biomarkers and their heterogeneity might affect diagnosis. We identified multimodal biomarkers distinguishing FMD... read more 

Integrating single-cell RNA and bulk RNA sequencing data to identify prognostic genes associated with pyrimidine metabolism in triple-negative breast cancer by machine learning algorithm combinations.

Discover oncology
BACKGROUND: Pyrimidine metabolism plays a crucial role in DNA synthesis and cell proliferation and is associated with the development of various cancers. However, their prognostic value in triple-negative breast cancer remains to be further investiga... read more 

Decoding the Black Box in Deep Learning Models-Reply.

JAMA otolaryngology-- head & neck surgery
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