Neural networks : the official journal of the International Neural Network Society
Dec 7, 2024
Self-supervised Learning (SSL) has been recognized as a method to enhance prediction accuracy in various downstream tasks. However, its efficacy for DNA sequences remains somewhat constrained. This limitation stems primarily from the fact that most e...
Journal of applied clinical medical physics
Dec 6, 2024
BACKGROUND AND OBJECTIVE: The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get bene...
BACKGROUND: Accurate and automatic segmentation of pericardial adipose tissue (PEAT) in cardiac magnetic resonance (MR) images is essential for the diagnosis and treatment of cardiovascular diseases. Precise segmentation is challenging due to high co...
BACKGROUND: Semi-supervised learning provides an effective means to address the challenge of insufficient labeled data in medical image segmentation tasks. However, when a semi-supervised segmentation model is overfitted and exhibits cognitive bias, ...
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine-tuning on downstream tasks with limited labeled examples. Self-pretraining is a SSL approach that uses curated do...
Traditional medical image sensors face multiple challenges. First, these sensors typically rely on large amounts of labeled data, which are time-consuming and costly to obtain. Second, when the data volume and image size are large, traditional sensor...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Self-supervised learning (SSL) reduces the need for manual annotation in deep learning models for medical image analysis. By learning the representations from unablelled data, self-supervised models perform well on tasks that require little to no fin...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Self-supervised learning (SSL) is a challenging task in sleep stage classification (SSC) that is capable of mining valuable representations from unlabeled data. However, traditional SSL methods typically focus on single-view learning and do not fully...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Molecular representation learning has remarkably accelerated the development of drug analysis and discovery. It implements machine learning methods to encode molecule embeddings for diverse downstream drug-related tasks. Due to the scarcity of labele...
IEEE journal of biomedical and health informatics
Dec 5, 2024
Pathological examination of nasopharyngeal carcinoma (NPC) is an indispensable factor for diagnosis, guiding clinical treatment and judging prognosis. Traditional and fully supervised NPC diagnosis algorithms require manual delineation of regions of ...