<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"><identifier identifierType="DOI">10.34820/FK2/QVCP6V</identifier><creators><creator><creatorName nameType="Personal">Adiwijaya</creatorName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0000-0002-3518-7587</nameIdentifier><affiliation>Telkom University</affiliation></creator><creator><creatorName nameType="Personal">NOVIA WISESTY, UNTARI</creatorName><givenName>UNTARI</givenName><familyName>NOVIA WISESTY</familyName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0000-0001-5803-9643</nameIdentifier><affiliation>Telkom University</affiliation></creator><creator><creatorName nameType="Personal">Widi Astuti</creatorName><nameIdentifier SchemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">0000-0002-7730-6134</nameIdentifier><affiliation>Telkom University</affiliation></creator></creators><titles><title>Polycystic Ovary Ultrasound Images Dataset</title></titles><publisher>Root</publisher><publicationYear>2021</publicationYear><subjects><subject>Computer and Information Science</subject><subject>Medicine, Health and Life Sciences</subject><subject>Polycystic Ovary (PCO)</subject><subject>Polycystic Ovary Syndrome (PCOS)</subject><subject>Ultrasound Images</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Organizational">NOVIA WISESTY, UNTARI</contributorName><affiliation>Telkom University</affiliation></contributor></contributors><dates><date dateType="Submitted">2021-03-04</date><date dateType="Updated">2021-03-04</date></dates><resourceType resourceTypeGeneral="Dataset"/><relatedIdentifiers><relatedIdentifier relationType="IsCitedBy" SchemeURI="https://doi.org/" relatedIdentifierType="DOI">10.3844/jcssp.2018.351.359</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" SchemeURI="https://doi.org/" relatedIdentifierType="DOI">10.1088/1742-6596/622/1/012027</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" SchemeURI="https://doi.org/" relatedIdentifierType="DOI">10.1007/978-3-319-51281-5_15</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" SchemeURI="https://doi.org/" relatedIdentifierType="DOI">10.1088/1742-6596/971/1/012016</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" SchemeURI="https://doi.org/" relatedIdentifierType="DOI">10.1088/1742-6596/971/1/012005</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" relatedIdentifierType="DOI">10.1109/ICoICT.2015.7231458</relatedIdentifier><relatedIdentifier relationType="IsCitedBy" relatedIdentifierType="DOI">10.1109/ICoICT.2015.7231453</relatedIdentifier></relatedIdentifiers><sizes><size>30538</size><size>29792</size><size>30260</size><size>29930</size><size>30746</size><size>29573</size><size>30324</size><size>29520</size><size>31328</size><size>29556</size><size>28722</size><size>31698</size><size>30855</size><size>30242</size><size>29245</size><size>31118</size><size>29739</size><size>30433</size><size>29867</size><size>30549</size><size>29670</size><size>30762</size><size>29975</size><size>30020</size><size>29917</size><size>30460</size><size>31119</size><size>29839</size><size>30741</size><size>29103</size><size>30264</size><size>30028</size><size>30098</size><size>29672</size><size>31249</size><size>31176</size><size>29635</size><size>30967</size><size>29431</size><size>30291</size><size>30092</size><size>29704</size><size>30588</size><size>29528</size><size>28833</size><size>30216</size><size>29127</size><size>30318</size><size>30754</size><size>29674</size><size>30708</size><size>30721</size><size>30192</size><size>30481</size></sizes><formats><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format><format>image/jpeg</format></formats><version>1.0</version><rightsList><rights rightsURI="info:eu-repo/semantics/openAccess"/><rights rightsURI="https://creativecommons.org/publicdomain/zero/1.0/">CC0 Waiver</rights></rightsList><descriptions><description descriptionType="Abstract">This dataset contains ultrasound images of patients suffering from Polycystic Ovary Syndrome (PCOS) and normal patients. Each image in the dataset has been categorized into PCOS and Normal classes, which are annotations from specialist doctors.</description></descriptions><geoLocations/></resource>