Artificial intelligence applied to diabetes complications: a bibliometric analysis.

Background And Aims: Artificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots.

Methodology: On April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed.

A novel approach for adaptively separating and extracting compound fault features of the in-wheel motor bearing.

For compound fault detection of in-wheel motor bearings, this paper proposes a novel approach to adaptively separate multi-source signals and extract compound fault features. Building upon blind source separation (BSS), this approach integrates blind deconvolution to address the challenge of extracting weak features. To resolve the undetermined condition of BSS and enhance feature expression, an adaptive signal reconstruction strategy based on local mean decomposition is proposed.