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AI in Neurology: Everything, Everywhere, All at Once Part 3: Surveillance, Synthesis, Simulation, and Systems

Annals of Neurology, EarlyView.
This final part 3 review builds on the practical applications discussed in part 2 and explores how artificial intelligence (AI) is transforming data management, neurological education, and neurological care across large healthcare networks and datasets. The review also highlights AI's role in real‐world and synthetic data, digital twins, and innovative
Matthew Rizzo
wiley   +1 more source

Analysis of plant metabolomics data using identification‐free approaches

Applications in Plant Sciences, EarlyView.
Abstract Plant metabolomes are structurally diverse. One of the most popular techniques for sampling this diversity is liquid chromatography–mass spectrometry (LC‐MS), which typically detects thousands of peaks from single organ extracts, many representing true metabolites.
Xinyu Yuan, Nathaniel S. S. Smith, Gaurav D. Moghe   +2 more
wiley   +1 more source

Chromosome‐scale reference genome of Pectocarya recurvata, the species with the smallest reported genome size in Boraginaceae

Applications in Plant Sciences, EarlyView.
Abstract Premise Pectocarya recurvata (Boraginaceae, subfamily Cynoglossoideae), a species native to the Sonoran Desert (North America), has served as a model system for a suite of ecological and evolutionary studies. However, no reference genomes are currently available in Cynoglossoideae. A high‐quality reference genome for P.
Poppy C. Northing, Jessie A. Pelosi, D. Lawrence Venable, Katrina M. Dlugosch   +3 more
wiley   +1 more source

Matching domain and top-level ontologies via OntoWordNet

, 2017
Daniela Schmidt, Rafael Basso, Cássia Trojahn dos Santos, Renata Vieira   +3 more
openalex   +1 more source

Local matching learning of large scale biomedical ontologies

, 2019
Amir Laadhar
openalex   +1 more source

Ontology matching in a distributed environment

, 2016
openaire   +3 more sources

Using NSGA‐III for optimising biomedical ontology alignment

CAAI Transactions on Intelligence Technology, 2019
To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts
Jiawei Lu, Xingsi Xue, Hong Quoc Nguyen
exaly   +3 more sources

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Efficient User Involvement in Semiautomatic Ontology Matching

IEEE Transactions on Emerging Topics in Computational Intelligence, 2021
Semiautomatic ontology matching poses a new challenge of how to implement an efficient user interactions. To address this challenge, we answer three questions in this paper: (1) when should we activate the interacting process; (2) which correspondences ...
Xingsi Xue, Junfeng Chen, Xin Yao
semanticscholar   +1 more source

MEDTO: Medical Data to Ontology Matching Using Hybrid Graph Neural Networks

Knowledge Discovery and Data Mining, 2021
Medical ontologies are widely used to describe and organize medical terminologies and to support many critical applications on healthcare databases. These ontologies are often manually curated (e.g., UMLS, SNOMED CT, and MeSH) by medical experts. Medical
Junheng Hao, Chuan Lei, Vasilis Efthymiou, A. Quamar, Fatma Özcan, Yizhou Sun, Wei Wang, Fatma, Özcan   +8 more
semanticscholar   +1 more source

Survey on complex ontology matching

Semantic Web, 2020
. Simple ontology alignments, largely studied in the literature, link a single entity of a source ontology to a single entity of a target ontology. One of the limitations of these alignments is, however, their lack of expressiveness which can be overcome
Élodie Thiéblin, Ollivier Haemmerlé, Nathalie Hernandez, C. Trojahn   +3 more
semanticscholar   +1 more source