Interpretable Machine Learning Models Using Peripheral Immune Cells to Predict 90-Day Readmission or Mortality in Acute Heart Failure Patients

Background Acute heart failure (AHF) carries a grave prognosis, marked by high readmission and mortality rates within 90 days post-discharge. This underscores the urgent need for enhanced care transitions, early monitoring, and precise interventions for at-risk individuals during this critical perio...

Ful tanımlama

Kaydedildi:

Detaylı Bibliyografya
Asıl Yazarlar:	Junming Chen BS, Liting Yang MS, Jiangchuan Han BS, Liang Wang MS, Tingting Wu BS, Dongsheng Zhao MS
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	SAGE Publishing 2024-05-01
Seri Bilgileri:	Clinical and Applied Thrombosis/Hemostasis
Online Erişim:	https://doi.org/10.1177/10760296241259784
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

Interpretable Machine Learning Models Using Peripheral Immune Cells to Predict 90-Day Readmission or Mortality in Acute Heart Failure Patients

Benzer Materyaller