Visual analysis of research trends and hotspots in wearable electronic devices in the medical field: A bibliometric study.

Background: Healthcare services and functionalities need comprehensive upgrades, and advancements in information technology have driven research in wearable electronic devices (WDs), making them critical tools for this purpose.

Objective: To conduct a systematic bibliometric analysis of WDs in the medical field and understand research trends.

Methods: A literature search of articles related to WDs in the medical field was conducted in the Web of Science Core Collection (WoSCC) from 2013 to 2023.

A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet+.

Objective: Radiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tumor are gradually increasing. Manual segmentation of normal hepatic tissue and tumor exhibits limitations.

Methods: 105 patients diagnosed with hepatocellular carcinoma were retrospectively studied between Jan 2015 and Dec 2020.