Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer.

Background: Synchronous liver metastasis (SLM) is a significant contributor to morbidity in colorectal cancer (CRC). There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC.

Aim: To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix (GLCM) features collected from magnetic resonance imaging (MRI).

A 5G-based telerobotic ultrasound system provides qualified abdominal ultrasound services for patients on a rural island: a prospective and comparative study of 401 patients.

Purpose: To explore the feasibility of a 5G-based telerobotic ultrasound (US) system for providing qualified abdominal US services on a rural island.

Methods: This prospective study involved two medical centers (the tele-radiologist site's hospital and the patient site's hospital) separated by 72 km. Patients underwent 5G-based telerobotic US by tele-radiologists and conventional US by on-site radiologists from September 2020 to March 2021.

Primary splenic angiosarcoma with liver metastasis: A case report and literature review.

Primary splenic angiosarcoma (PSA) is an unusual and highly malignant vascular tumour with a high rate of metastatic. Moreover, the research on prognosis of the disease is poor. The epidemiology, etiology, clinical diagnosis and treatment of the disease remain challenging, because case reports of the disease are few in number.