Your browser doesn't support javascript.
MedSentinel - A Smart Sentinel for Biomedical Online Search Demonstrated by a COVID-19 Search.
Schölly, Reto; Yazijy, Suhail; Kellmeyer, Philipp.
  • Schölly R; University Medical Center Freiburg, Department of Neurosurgery, Neuroethics and AI Ethics Lab, Breisacher Str. 64, D-79106 Freiburg i. Br. (Germany).
  • Yazijy S; University Medical Center Freiburg, Department of Neurosurgery, Neuroethics and AI Ethics Lab, Breisacher Str. 64, D-79106 Freiburg i. Br. (Germany).
  • Kellmeyer P; University Medical Center Freiburg, Department of Neurosurgery, Neuroethics and AI Ethics Lab, Breisacher Str. 64, D-79106 Freiburg i. Br. (Germany).
Stud Health Technol Inform ; 290: 278-281, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933556
ABSTRACT
We present a work-in-progress software project which aims to assist cross-database medical research and knowledge acquisition from heterogeneous sources. Using a Natural Language Processing (NLP) model based on deep learning algorithms, topical similarities are detected, going beyond measures of connectivity via citation or database suggestion algorithms. A network is generated based on the NLP-similarities between them, and then presented within an explorable 3D environment. Our software will then generate a list of publications and datasets which pertain to a certain topic of interest, based on their level of similarity in terms of knowledge representation.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Randomized controlled trials Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Randomized controlled trials Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article