METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING
FIELD: computing technology.SUBSTANCE: invention relates to a method for building a classifier of pathogenicity of variants. Also to a method for building a classifier based on a convolutional neural network for classifying variants, implemented by means of a computer, to computer-readable long-term...
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| creator | SUNDARAM, Laksshman MAKREJ, Dzheremi Frensis FARKH, Kaj-Khou GAO, Khun |
| description | FIELD: computing technology.SUBSTANCE: invention relates to a method for building a classifier of pathogenicity of variants. Also to a method for building a classifier based on a convolutional neural network for classifying variants, implemented by means of a computer, to computer-readable long-term information storage media and systems including one or multiple processors associated with memory.EFFECT: provided classification of pathogenicity of variants by means of a neural network.23 cl, 1 ex, 66 dwg, 8 tbl
Изобретение относится к способу построения классификатора патогенности вариантов. А также к способу построения классификатора на основе сверточной нейронной сети для классификации вариантов, реализуемому при помощи компьютера, компьютерочитаемым носителям долговременного хранения информации и системам, включающим один или несколько процессоров, связанных с памятью. 6 н. и 17 з.п. ф-лы, 1 пр., 66 ил., 8 табл. |
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Изобретение относится к способу построения классификатора патогенности вариантов. А также к способу построения классификатора на основе сверточной нейронной сети для классификации вариантов, реализуемому при помощи компьютера, компьютерочитаемым носителям долговременного хранения информации и системам, включающим один или несколько процессоров, связанных с памятью. 6 н. и 17 з.п. ф-лы, 1 пр., 66 ил., 8 табл.</description><language>eng ; rus</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; HANDLING RECORD CARRIERS ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220317&DB=EPODOC&CC=RU&NR=2767337C2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25562,76317</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220317&DB=EPODOC&CC=RU&NR=2767337C2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>SUNDARAM, Laksshman</creatorcontrib><creatorcontrib>MAKREJ, Dzheremi Frensis</creatorcontrib><creatorcontrib>FARKH, Kaj-Khou</creatorcontrib><creatorcontrib>GAO, Khun</creatorcontrib><title>METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING</title><description>FIELD: computing technology.SUBSTANCE: invention relates to a method for building a classifier of pathogenicity of variants. Also to a method for building a classifier based on a convolutional neural network for classifying variants, implemented by means of a computer, to computer-readable long-term information storage media and systems including one or multiple processors associated with memory.EFFECT: provided classification of pathogenicity of variants by means of a neural network.23 cl, 1 ex, 66 dwg, 8 tbl
Изобретение относится к способу построения классификатора патогенности вариантов. А также к способу построения классификатора на основе сверточной нейронной сети для классификации вариантов, реализуемому при помощи компьютера, компьютерочитаемым носителям долговременного хранения информации и системам, включающим один или несколько процессоров, связанных с памятью. 6 н. и 17 з.п. ф-лы, 1 пр., 66 ил., 8 табл.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>HANDLING RECORD CARRIERS</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPDzdQ3x8HcJVnDzD1IICXL09PP0c1dwcXUNUHD29wvz9wkN8fT3c_RR8HMNDQJTIeH-Qd7BCk6Owa4uCv5-ELU-ro5BIJ08DKxpiTnFqbxQmptBwc01xNlDN7UgPz61uCAxOTUvtSQ-KNTI3Mzc2Njc2ciYCCUAzYQuXQ</recordid><startdate>20220317</startdate><enddate>20220317</enddate><creator>SUNDARAM, Laksshman</creator><creator>MAKREJ, Dzheremi Frensis</creator><creator>FARKH, Kaj-Khou</creator><creator>GAO, Khun</creator><scope>EVB</scope></search><sort><creationdate>20220317</creationdate><title>METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING</title><author>SUNDARAM, Laksshman ; MAKREJ, Dzheremi Frensis ; FARKH, Kaj-Khou ; GAO, Khun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_RU2767337C23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; rus</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>HANDLING RECORD CARRIERS</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><toplevel>online_resources</toplevel><creatorcontrib>SUNDARAM, Laksshman</creatorcontrib><creatorcontrib>MAKREJ, Dzheremi Frensis</creatorcontrib><creatorcontrib>FARKH, Kaj-Khou</creatorcontrib><creatorcontrib>GAO, Khun</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>SUNDARAM, Laksshman</au><au>MAKREJ, Dzheremi Frensis</au><au>FARKH, Kaj-Khou</au><au>GAO, Khun</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING</title><date>2022-03-17</date><risdate>2022</risdate><abstract>FIELD: computing technology.SUBSTANCE: invention relates to a method for building a classifier of pathogenicity of variants. Also to a method for building a classifier based on a convolutional neural network for classifying variants, implemented by means of a computer, to computer-readable long-term information storage media and systems including one or multiple processors associated with memory.EFFECT: provided classification of pathogenicity of variants by means of a neural network.23 cl, 1 ex, 66 dwg, 8 tbl
Изобретение относится к способу построения классификатора патогенности вариантов. А также к способу построения классификатора на основе сверточной нейронной сети для классификации вариантов, реализуемому при помощи компьютера, компьютерочитаемым носителям долговременного хранения информации и системам, включающим один или несколько процессоров, связанных с памятью. 6 н. и 17 з.п. ф-лы, 1 пр., 66 ил., 8 табл.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | METHODS FOR TRAINING DEEP CONVOLUTIONAL NEURAL NETWORKS BASED ON DEEP LEARNING |
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