A comprehensive review of deep learning-based models for heart disease prediction
C Zhou, P Dai, A Hou, Z Zhang, L Liu, A Li… - Artificial Intelligence …, 2024 - Springer
Heart disease (HD) is one of the leading causes of death in humans, posing a heavy burden
on society, families, and patients. Real-time prediction of HD can reduce mortality rates and …
on society, families, and patients. Real-time prediction of HD can reduce mortality rates and …
Novel strategies to improve prescription of guideline-directed medical therapy in heart failure
JA Brooksbank, KD Faulkenberg, WHW Tang… - … Treatment Options in …, 2023 - Springer
Purpose of review To examine the emerging data for novel strategies being studied to
improve use and dose titration of guideline-directed medical therapy (GDMT) for patients …
improve use and dose titration of guideline-directed medical therapy (GDMT) for patients …
Heart failure diagnosis in the general community–Who, how and when? A clinical consensus statement of the Heart Failure Association (HFA) of the European Society …
KF Docherty, CSP Lam, A Rakisheva… - European Journal of …, 2023 - Wiley Online Library
A significant proportion of patients experience delays in the diagnosis of heart failure due to
the non‐specific signs and symptoms of the syndrome. Diagnostic tools such as …
the non‐specific signs and symptoms of the syndrome. Diagnostic tools such as …
A scoping review of electronic health records–based screening algorithms for familial hypercholesterolemia
Background Familial hypercholesterolemia (FH) is a common genetic disorder that is
strongly associated with premature cardiovascular disease. Effective diagnosis and …
strongly associated with premature cardiovascular disease. Effective diagnosis and …
VAE-Driven Multimodal Fusion for Early Cardiac Disease Detection
J Wang, J Li, R Wang, X Zhou - IEEE Access, 2024 - ieeexplore.ieee.org
This study presents a novel multimodal deep learning model designed to improve early
detection and diagnosis of chronic cardiac conditions such as Severe Left Ventricular …
detection and diagnosis of chronic cardiac conditions such as Severe Left Ventricular …
[HTML][HTML] Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep …
Z Gao, X Liu, Y Kang, P Hu, X Zhang, W Yan… - Journal of Medical …, 2024 - jmir.org
Background Clinical notes contain contextualized information beyond structured data
related to patients' past and current health status. Objective This study aimed to design a …
related to patients' past and current health status. Objective This study aimed to design a …
Recent advancements and applications of deep learning in heart failure: Α systematic review
G Petmezas, VE Papageorgiou, V Vassilikos… - Computers in Biology …, 2024 - Elsevier
Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …
management approaches. The rapid evolution of deep learning (DL) in healthcare …
AI-based models to predict decompensation on traumatic brain injury patients
R Ribeiro, I Neves, HP Oliveira, T Pereira - Computers in Biology and …, 2025 - Elsevier
Abstract Traumatic Brain Injury (TBI) is a form of brain injury caused by external forces,
resulting in temporary or permanent impairment of brain function. Despite advancements in …
resulting in temporary or permanent impairment of brain function. Despite advancements in …
Predicting heart failure in-hospital mortality by integrating longitudinal and category data in electronic health records
M Ma, X Hao, J Zhao, S Luo, Y Liu, D Li - Medical & Biological …, 2023 - Springer
Heart failure is a life-threatening syndrome that is diagnosed in 3.6 million people worldwide
each year. We propose a deep fusion learning model (DFL-IMP) that uses time series and …
each year. We propose a deep fusion learning model (DFL-IMP) that uses time series and …
Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data
Timely and accurate referral of end-stage heart failure patients for advanced therapies,
including heart transplants and mechanical circulatory support, plays an important role in …
including heart transplants and mechanical circulatory support, plays an important role in …