Organ segmentation in abdominal or thoracic computed tomography (CT) images plays a crucial role in medical diagnosis as it enables doctors to locate and evaluate organ abnormalities quickly, thereby guiding surgical planning, and aiding treatment de...
In this paper, we present a novel algorithm that uses machine learning and natural language processing techniques to facilitate the coding of feature listing data. Feature listing is a method in which participants are asked to provide a list of featu...
BACKGROUND: Ontologies play a key role in the management of medical knowledge because they have the properties to support a wide range of knowledge-intensive tasks. The dynamic nature of knowledge requires frequent changes to the ontologies to keep t...
Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access ...
PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy design, with some models proposed for detecting oral pharyngeal, nasopharyngeal, or laryngeal carcinoma. However, no comprehensive model has been estab...
This study focuses on ischaemia-reperfusion injury (IRI) in kidneys, a cause of acute kidney injury (AKI) and end-stage kidney disease (ESKD). Traditional kidney damage assessment methods are semi-quantitative and subjective. This study aims to use a...
BACKGROUND AIMS: Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, ther...
Neural networks : the official journal of the International Neural Network Society
Sep 11, 2023
Contrastive learning methods aim to learn shared representations by minimizing distances between positive pairs, and maximizing distances between negative pairs in the embedding space. To achieve better performance of contrastive learning, one of the...
IEEE journal of biomedical and health informatics
Sep 6, 2023
Medical image segmentation, or computing voxel-wise semantic masks, is a fundamental yet challenging task in medical imaging domain. To increase the ability of encoder-decoder neural networks to perform this task across large clinical cohorts, contra...