BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new artificial intelligence algorithms are opening up new opportunities for electrophysiological knowle...
Journal of applied clinical medical physics
Feb 13, 2025
PURPOSE: Deep learning-based segmentation of organs-at-risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model-based autocontouring methods. While several commercial deep learning-base...
Causal machine learning is an approach that combines causal inference and machine learning to understand and utilize causal relationships in data. In current research and applications, traditional machine learning and deep learning models always focu...
BMC medical informatics and decision making
Feb 13, 2025
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) represents a significant global health challenge, placing considerable burdens on healthcare systems. The rise of digital health technologies (DHTs) and artificial intelligence (AI) algorithms ...
Normative representation learning focuses on understanding the typical anatomical distributions from large datasets of medical scans from healthy individuals. Generative Artificial Intelligence (AI) leverages this attribute to synthesize images that ...
Named Entity Recognition for crop diseases and pests (NER-CDP) is significant in agricultural information extraction and offers vital data support for subsequent knowledge services and retrieval. However, existing NER-CDP methods rely heavily on plai...
Inferring and understanding the underlying connectivity structure of a system solely from the observed activity of its constituent components is a challenge in many areas of science. In neuroscience, techniques for estimating connectivity are paramou...
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Feb 13, 2025
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.
Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approac...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 13, 2025
This study presents a novel wearable solution integrating Polymer Optical Fiber (POF) sensors into a knee sleeve to monitor knee flexion/extension (F/E) patterns during walking. POF sensors offer advantages such as flexibility, light weight, and robu...
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