Predicting brain age using Tri-UNet and various MRI scale features
Y Pang, Y Cai, Z Xia, X Gao - Scientific Reports, 2024 - nature.com
In the process of human aging, significant age-related changes occur in brain tissue. To
assist individuals in assessing the degree of brain aging, screening for disease risks, and …
assist individuals in assessing the degree of brain aging, screening for disease risks, and …
Cancer: Investigating the impact of the implementation platform on machine learning models
AS Olowolayemo, A Souag… - AIHealth 2024, The …, 2024 - repository.canterbury.ac.uk
In the context of global cancer prevalence and the imperative need to improve diagnostic
efficiency, scientists have turned to machine learning (ML) techniques to expedite diagnosis …
efficiency, scientists have turned to machine learning (ML) techniques to expedite diagnosis …
Tri-UNet: A Brain Age Prediction Method Based on Different Scale Features of Magnetic Resonance Imaging
Y Pang, Y Cai - 2024 - researchsquare.com
In the process of human aging, significant age-related changes occur in brain tissue. To
assist individuals in assessing the degree of brain aging, screening for disease risks, and …
assist individuals in assessing the degree of brain aging, screening for disease risks, and …
Multimodal Deep Learning for Classifying Diabetes: Analyzing Carotid Ultrasound Images from UK and Taiwan Biobanks and Their Cardiovascular Disease …
Objective Clinical evidence has shown that carotid intima-media thickness (CIMT) is a robust
biomarker for determining the thickness of atherosclerosis, which in turn increases the risk of …
biomarker for determining the thickness of atherosclerosis, which in turn increases the risk of …