AIMC Topic: Artificial Intelligence

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The scientific progress and prospects of artificial intelligence in digestive endoscopy: A comprehensive bibliometric analysis.

Medicine
Artificial intelligence (AI) has been used for diagnosis and outcome prediction in clinical practice. Furthermore, AI in digestive endoscopy has attracted much attention and shown promising and stimulating results. This study aimed to determine the d...

Deep learning identifies explainable reasoning paths of mechanism of action for drug repurposing from multilayer biological network.

Briefings in bioinformatics
The discovery and repurposing of drugs require a deep understanding of the mechanism of drug action (MODA). Existing computational methods mainly model MODA with the protein-protein interaction (PPI) network. However, the molecular interactions of dr...

Machine learning alternative to systems biology should not solely depend on data.

Briefings in bioinformatics
In recent years, artificial intelligence (AI)/machine learning has emerged as a plausible alternative to systems biology for the elucidation of biological phenomena and in attaining specified design objective in synthetic biology. Although considered...

Artificial intelligence-driven prediction of multiple drug interactions.

Briefings in bioinformatics
When a drug is administered to exert its efficacy, it will encounter multiple barriers and go through multiple interactions. Predicting the drug-related multiple interactions is critical for drug development and safety monitoring because it provides ...

A geometric deep learning framework for drug repositioning over heterogeneous information networks.

Briefings in bioinformatics
Drug repositioning (DR) is a promising strategy to discover new indicators of approved drugs with artificial intelligence techniques, thus improving traditional drug discovery and development. However, most of DR computational methods fall short of t...

Multi-modality artificial intelligence in digital pathology.

Briefings in bioinformatics
In common medical procedures, the time-consuming and expensive nature of obtaining test results plagues doctors and patients. Digital pathology research allows using computational technologies to manage data, presenting an opportunity to improve the ...

Effects of ai-assisted colonoscopy on adenoma miss rate/adenoma detection rate: A protocol for systematic review and meta-analysis.

Medicine
BACKGROUND: Colonoscopy can detect colorectal adenomas and reduce the incidence of colorectal cancer, but there are still many missing diagnoses. Artificial intelligence-assisted colonoscopy (AIAC) can effectively reduce the rate of missed diagnosis ...

Picture a data scientist: a call to action for increasing diversity, equity, and inclusion in the age of AI.

Journal of the American Medical Informatics Association : JAMIA
The lack of diversity, equity, and inclusion continues to hamper the artificial intelligence (AI) field and is especially problematic for healthcare applications. In this article, we expand on the need for diversity, equity, and inclusion, specifical...

Differentiation of breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using deep transfer learning based on DenseNet201.

Medicine
In order to achieve better performance, artificial intelligence is used in breast cancer diagnosis. In this study, we evaluated the efficacy of different fine-tuning strategies of deep transfer learning (DTL) based on the DenseNet201 model to differe...