AIMC Topic: Humans

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Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies.

BMC medical informatics and decision making
BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. W...

Analysis of readability and structural accuracy in SNOMED CT.

BMC medical informatics and decision making
BACKGROUND: The increasing adoption of ontologies in biomedical research and the growing number of ontologies available have made it necessary to assure the quality of these resources. Most of the well-established ontologies, such as the Gene Ontolog...

Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry.

BMC medical informatics and decision making
BACKGROUND: The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. a...

Quality assurance and enrichment of biological and biomedical ontologies and terminologies.

BMC medical informatics and decision making
Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The growing number of such ontologies and termino...

Artificial Intelligence in the Fight Against COVID-19: Scoping Review.

Journal of medical Internet research
BACKGROUND: In December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been...

Exploring a Structural Basis for Delayed Rod-Mediated Dark Adaptation in Age-Related Macular Degeneration Via Deep Learning.

Translational vision science & technology
PURPOSE: Delayed rod-mediated dark adaptation (RMDA) is a functional biomarker for incipient age-related macular degeneration (AMD). We used anatomically restricted spectral domain optical coherence tomography (SD-OCT) imaging data to localize de nov...

Fully Automatic Atrial Fibrosis Assessment Using a Multilabel Convolutional Neural Network.

Circulation. Cardiovascular imaging
BACKGROUND: Pathological atrial fibrosis is a major contributor to sustained atrial fibrillation. Currently, late gadolinium enhancement (LGE) scans provide the only noninvasive estimate of atrial fibrosis. However, widespread adoption of atrial LGE ...

Imbalanced learning: Improving classification of diabetic neuropathy from magnetic resonance imaging.

PloS one
One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply ove...

Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection.

PloS one
The coronavirus disease (COVID-19), is an ongoing global pandemic caused by severe acute respiratory syndrome. Chest Computed Tomography (CT) is an effective method for detecting lung illnesses, including COVID-19. However, the CT scan is expensive a...