Related Experiment Video
Updated: Jul 5, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Doctors' original intentionality in adherence to non-invasive diagnoses benefits MAFLD patients]
1Department of Biostatistics and Records Room, Medical Quality Management Office, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China Department of Hepatology, MAFLD Research Center, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Abstract:
Precisely diagnosing metabolic dysfunction-associated fatty liver disease (MAFLD) and its severity degree can effectively delay disease progression and have important guiding values for treatment. In recent years, research on non-invasive diagnosis of metabolic dysfunction-associated fatty liver disease has made great progress, suggesting that we should not only give full play advantage to professional personnel in the field of liver disease but also actively cooperate with personnel in other fields to explore different high-performance non-invasive diagnostic methods to achieve early detection, diagnosis, and treatment.
More Related Videos
13:12Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
Published on: August 12, 2019
08:33Olfactory Neurons Obtained through Nasal Biopsy Combined with Laser-Capture Microdissection: A Potential Approach to Study Treatment Response in Mental Disorders
Published on: December 4, 2014