The clinical application of detecting COVID-19 factors is a challenging task. The existing named entity recognition models are usually trained on a limited set of named entities. Besides clinical, the non-clinical factors, such as social determinant ...
International journal of medical informatics
Dec 10, 2022
BACKGROUND: As opioid prescriptions have risen, there has also been an increase in opioid use disorder (OUD) and its adverse outcomes. Accurate and complete epidemiologic surveillance of OUD, to inform prevention strategies, presents challenges. The ...
BACKGROUND: Obesity is a leading cause of preventable death worldwide. Artificial intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has become an indispensable tool in obesity research.
The automatic extraction of procedural surgical knowledge from surgery manuals, academic papers or other high-quality textual resources, is of the utmost importance to develop knowledge-based clinical decision support systems, to automatically execut...
IEEE transactions on pattern analysis and machine intelligence
Dec 5, 2022
Connecting Vision and Language plays an essential role in Generative Intelligence. For this reason, large research efforts have been devoted to image captioning, i.e. describing images with syntactically and semantically meaningful sentences. Startin...
Researchers and practitioners are often interested in assessing employee attitudes and work perceptions. Although such perceptions are typically measured using Likert surveys or some other closed-end numerical rating format, many organizations also h...
The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an incidence that has not changed over the last 30 years, ADRs are a significant source of patient morbidity, ...
IEEE transactions on neural networks and learning systems
Nov 30, 2022
A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted ...
UNLABELLED: is to create, train, and test the algorithm for the analysis of brain CT text reports using a decision tree model to solve the task of simple binary classification of presence/absence of intracranial hemorrhage (ICH) signs.
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