AIMC Topic: Semantics

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Surgical instrument segmentation based on multi-scale and multi-level feature network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Surgical instrument segmentation is critical for the field of computer-aided surgery system. Most of deep-learning based algorithms only use either multi-scale information or multi-level information, which may lead to ambiguity of semantic informatio...

Understanding the Gap Between Information Models and Realism-Based Ontologies Using the Generic Component Model.

Studies in health technology and informatics
The wide-spread use of Common Data Models and information models in biomedical informatics encourages assumptions that those models could provide the entirety of what is needed for knowledge representation purposes. Based on the lack of computable se...

A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information.

Briefings in bioinformatics
Recently, language representation models have drawn a lot of attention in the natural language processing field due to their remarkable results. Among them, bidirectional encoder representations from transformers (BERT) has proven to be a simple, yet...

Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.

Briefings in bioinformatics
As an essential task in protein structure and function prediction, protein fold recognition has attracted increasing attention. The majority of the existing machine learning-based protein fold recognition approaches strongly rely on handcrafted featu...

Semantic image segmentation of brain MRI with deep learning.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: Previous studies on brain MRI image segmentation, such as threshold method, boundary detection method, and region method did not achieve good performance in complex scenes. Based on the deep learning segmentation technology, this study co...

PharmKG: a dedicated knowledge graph benchmark for bomedical data mining.

Briefings in bioinformatics
Biomedical knowledge graphs (KGs), which can help with the understanding of complex biological systems and pathologies, have begun to play a critical role in medical practice and research. However, challenges remain in their embedding and use due to ...

Semantic similarity and machine learning with ontologies.

Briefings in bioinformatics
Ontologies have long been employed in the life sciences to formally represent and reason over domain knowledge and they are employed in almost every major biological database. Recently, ontologies are increasingly being used to provide background kno...

Deep-learning-based automated terminology mapping in OMOP-CDM.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Accessing medical data from multiple institutions is difficult owing to the interinstitutional diversity of vocabularies. Standardization schemes, such as the common data model, have been proposed as solutions to this problem, but such sch...

Machine Scoring of Medical Students' Written Clinical Reasoning: Initial Validity Evidence.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: Developing medical students' clinical reasoning requires a structured longitudinal curriculum with frequent targeted assessment and feedback. Performance-based assessments, which have the strongest validity evidence, are currently not feasib...

Towards a Semantic Data Harmonization Federated Infrastructure.

Studies in health technology and informatics
Data integration is an increasing need in medical informatics projects like the EU Precise4Q project, in which multidisciplinary semantically and syntactically heterogeneous data across several institutions needs to be integrated. Besides, data shari...