2 results match your criteria International Journal of Intelligence Science

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Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

BMJ 2020 03 25;368:m689. Epub 2020 Mar 25.

Cera Care, London, UK.

Objective: To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep learning algorithms for medical imaging with that of expert clinicians.

Design: Systematic review.

Data Sources: Medline, Embase, Cochrane Central Register of Controlled Trials, and the World Health Organization trial registry from 2010 to June 2019. Read More

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http://dx.doi.org/10.1136/bmj.m689DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190037PMC

Converting Instance Checking to Subsumption: A Rethink for Object Queries over Practical Ontologies.

Int J Intell Sci 2015 Jan;5(1):44-62

Department of Electrical and Computer Engineering, University of Miami, Coral Gables, USA.

Efficiently querying Description Logic (DL) ontologies is becoming a vital task in various data-intensive DL applications. Considered as a basic service for answering object queries over DL ontologies, instance checking can be realized by using the most specific concept (MSC) method, which converts instance checking into subsumption problems. This method, however, loses its simplicity and efficiency when applied to large and complex ontologies, as it tends to generate very large MSCs that could lead to intractable reasoning. Read More

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http://dx.doi.org/10.4236/ijis.2015.51005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4652860PMC
January 2015
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