Medical informed machine learning: A sco** review and future research directions
Combining domain knowledge (DK) and machine learning is a recent research stream to
overcome multiple issues like limited explainability, lack of data, and insufficient robustness …
overcome multiple issues like limited explainability, lack of data, and insufficient robustness …
[HTML][HTML] Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation
Atrial fibrillation (AF) is a complex condition caused by various underlying
pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting …
pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting …
Sparse learned kernels for interpretable and efficient medical time series processing
Rapid, reliable and accurate interpretation of medical time series signals is crucial for high-
stakes clinical decision-making. Deep learning methods offered unprecedented …
stakes clinical decision-making. Deep learning methods offered unprecedented …
Deep learning for personalized electrocardiogram diagnosis: A review
The electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its
interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep …
interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep …
Tinyml design contest for life-threatening ventricular arrhythmia detection
The first ACM/IEEE TinyML Design Contest (TDC) held at the 41st International Conference
on Computer-Aided Design (ICCAD) in 2022 is a challenging, multimonth, research and …
on Computer-Aided Design (ICCAD) in 2022 is a challenging, multimonth, research and …
Few-shot transfer learning for personalized atrial fibrillation detection using patient-based siamese network with single-lead ECG records
Y Ng, MT Liao, TL Chen, CK Lee, CY Chou… - Artificial Intelligence in …, 2023 - Elsevier
The proliferation of wearable devices has allowed the collection of electrocardiogram (ECG)
recordings daily to monitor heart rhythm and rate. For example, 24-hour Holter monitors …
recordings daily to monitor heart rhythm and rate. For example, 24-hour Holter monitors …
Early prediction of heart disease via LSTM-XGBoost
X Zang, J Du, Y Song - Proceedings of the 2023 9th international …, 2023 - dl.acm.org
With the development of information and technology, especially with the boom in big data,
healthcare support systems are becoming much better. However, an early diagnosis is not …
healthcare support systems are becoming much better. However, an early diagnosis is not …
Personalized Deep Learning for IoT-Enabled Health Monitoring
Z Jia - 2022 - search.proquest.com
Biomedical sensors have been widely utilized to perform long-term health monitoring on
biosignals by being embedded into Internet-of-Things (IoT) devices. IoT-enabled health …
biosignals by being embedded into Internet-of-Things (IoT) devices. IoT-enabled health …
[PDF][PDF] Supplementary Material Advancing personalised care in atrial fibrillation and stroke: the potential impact of AI from prevention to rehabilitation
There are sex differences in AF across the scope of the disease pathway and its related
adverse outcomes (ie, stroke), from epidemiology and causative mechanisms to …
adverse outcomes (ie, stroke), from epidemiology and causative mechanisms to …