Our Projects | Data Science | Center for Precision Medicine and Data Sciences

Multi-organ crosstalk in HFpEF: Reframing a cardiac syndrome as a widespread systemic disease

A new article in The Journal of Precision Medicine: Health and Disease reframes heart failure with preserved ejection fraction (HFpEF) as a complex, systemic condition shaped by communication among multiple organs.

The authors explore how the heart interacts with the kidneys, lungs, liver, adipose tissue, skeletal muscle, vascular system, and immune system — revealing why HFpEF’s diverse biological pathways and patient presentations may require more personalized approaches to screening and treatment.

Center for Precision Medicine and Data Sciences members Martin Cadeiras and David A. Liem, have co-authored this important perspective with Clodomir Santana.

By examining the full network of organ-to-organ interactions, this work helps move the field toward more precise, phenotype-specific strategies for understanding and treating HFpEF.

Learn more

Most clinicians and health informaticians would agree that doctors’ written notes are one of the most important datasets in patient care. As such notes are recorded in natural language, traditional analytics cannot systematically derive meaning from them. Our goal is to apply natural language processing (NLP), a branch of machine learning, and NLP models such Bidirectional Encoder Representations from Transformers (BERT) to distill such notes into pertinent insights in a de-identified fashion that would be instrumental in promoting the next wave of clinical innovation.