Improving cardiovascular risk prediction with machine learning: a focus on perivascular adipose tissue characteristics.

Journal: Biomedical engineering online
Published Date:

Abstract

BACKGROUND: Timely prevention of major adverse cardiovascular events (MACEs) is imperative for reducing cardiovascular diseases-related mortality. Perivascular adipose tissue (PVAT), the adipose tissue surrounding coronary arteries, has attracted increased amounts of attention. Developing a model for predicting the incidence of MACE utilizing machine learning (ML) integrating clinical and PVAT features may facilitate targeted preventive interventions and improve patient outcomes.

Authors

  • Cong He
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Fangye Wu
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Linfeng Fu
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Lingting Kong
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Zefeng Lu
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Yingpeng Qi
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China.
  • Hongwei Xu
    Department of Radiology, Shaoxing Second Hospital, 123 Yanan Rd, Shaoxing, 312000, Zhejiang, China. chinaxhw@163.com.