Decoding the inflammatory-metabolic code: machine learning potential for outcome prediction in heart failure with diabetes.

Int J Cardiol

Université de Lorraine, Centre d'Investigations Cliniques Plurithématique 1433 and Inserm U1116, CHRU Nancy, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France.. Electronic address:

Published: August 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijcard.2025.133828DOI Listing

Publication Analysis

Top Keywords

decoding inflammatory-metabolic
4
inflammatory-metabolic code
4
code machine
4
machine learning
4
learning potential
4
potential outcome
4
outcome prediction
4
prediction heart
4
heart failure
4
failure diabetes
4

Similar Publications

Recording and Decoding of Vagal Neural Signals Related to Changes in Physiological Parameters and Biomarkers of Disease.

Cold Spring Harb Perspect Med

December 2019

Center for Bioelectronic Medicine, The Feinstein Institute for Medical Research, Donald & Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York 11030.

Our bodies have built-in neural reflexes that continuously monitor organ function and maintain physiological homeostasis. Whereas the field of bioelectronic medicine has mainly focused on the stimulation of neural circuits to treat various conditions, recent studies have started to investigate the possibility of leveraging the sensory arm of these reflexes to diagnose disease states. To accomplish this, neural signals emanating from the body's built-in biosensors and propagating through peripheral nerves must be recorded and decoded to identify the presence or levels of relevant biomarkers of disease.

View Article and Find Full Text PDF