Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.
Nat Commun
; 12(1): 3726, 2021 06 17.
Article
in English
| MEDLINE | ID: covidwho-1275922
ABSTRACT
High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
Nanopores
/
Machine Learning
/
COVID-19 Nucleic Acid Testing
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Nat Commun
Journal subject:
Biology
/
Science
Year:
2021
Document Type:
Article
Affiliation country:
S41467-021-24001-2
Similar
MEDLINE
...
LILACS
LIS