{ "@graph" : [ { "@id" : "http://semantics.gr/authorities/EKT-voc-classifier/605963148", "@type" : "skos:Concept", "broader" : "http://semantics.gr/authorities/EKT-voc-classifier/1532468312", "closeMatch" : "http://id.loc.gov/authorities/subjects/sh94004659", "exactMatch" : [ "http://id.loc.gov/authorities/subjects/sh85008180", "http://vocabularies.unesco.org/thesaurus/concept3052", "http://semantics.gr/authorities/EKT-voc/605963148" ], "note" : { "@language" : "en", "@value" : "isi - Computer Science, Artificial Intelligence covers resources that focus on research and techniques to create machines that attempt to efficiently reason, problem-solve, use knowledge representation, and perform analysis of contradictory or ambiguous information. This category includes resources on artificial intelligence technologies such as expert systems, fuzzy systems, natural language processing, speech recognition, pattern recognition, computer vision, decision-support systems, knowledge bases, and neural networks." }, "prefLabel" : [ { "@language" : "en", "@value" : "Artificial Intelligence" }, { "@language" : "el", "@value" : "Τεχνητή νοημοσύνη" } ], "relatedMatch" : [ "http://id.loc.gov/authorities/subjects/sh85031234", "http://id.loc.gov/authorities/subjects/sh85079324" ] }, { "@id" : "http://semantics.gr/authorities/openarchives-item-types/metaptyxiakh-ergasia", "@type" : "skos:Concept", "broader" : "http://semantics.gr/authorities/openarchives-item-types/Research-Paper-", "exactMatch" : "http://vocab.getty.edu/aat/300077723", "prefLabel" : [ { "@language" : "en", "@value" : "Master thesis" }, { "@language" : "el", "@value" : "Μεταπτυχιακή εργασία" } ] }, { "@id" : "https://www.openarchives.gr/aggregator-openarchives/edm/aggregation/provider/000004-2159_29441%231", "@type" : "ore:Aggregation", "aggregatedCHO" : "https://www.openarchives.gr/aggregator-openarchives/edm/psepheda/000004-2159_29441", "dataProvider" : "Πανεπιστήμιο Μακεδονίας", "isShownAt" : "https://dspace.lib.uom.gr/handle/2159/29441", "provider" : "Greek Aggregator OpenArchives.gr | National Documentation Centre (EKT)", "edm:rights" : { "@id" : "http://creativecommons.org/publicdomain/zero/1.0/" } }, { "@id" : "https://www.openarchives.gr/aggregator-openarchives/edm/psepheda/000004-2159_29441", "@type" : "edm:ProvidedCHO", "contributor" : { "@language" : "el", "@value" : "Χρήστου Βαρσακέλης, Δημήτριος" }, "creator" : { "@language" : "el", "@value" : "Μπαλκούδη, Μιχαέλα" }, "description" : [ { "@language" : "en", "@value" : "Made available in DSpace on 2023-10-06T07:41:37Z (GMT). No. of bitstreams: 2\nlicense_rdf: 701 bytes, checksum: 42fd4ad1e89814f5e4a476b409eb708c (MD5)\nΜπαλκούδηΜιχαέλαMSc2023.pdf.pdf: 1189968 bytes, checksum: 093e4efbd479c424e80b1c312cfaef82 (MD5)\n Previous issue date: 2023-08-29" }, { "@language" : "en", "@value" : "Approved for entry into archive by Κυριακή Μπαλτά (balta@uom.gr) on 2023-10-06T07:41:37Z (GMT) No. of bitstreams: 2\nlicense_rdf: 701 bytes, checksum: 42fd4ad1e89814f5e4a476b409eb708c (MD5)\nΜπαλκούδηΜιχαέλαMSc2023.pdf.pdf: 1189968 bytes, checksum: 093e4efbd479c424e80b1c312cfaef82 (MD5)" }, { "@language" : "en", "@value" : "Submitted by ΜΙΧΑΕΛΑ ΜΠΑΛΚΟΥΔΗ (aid21011@uom.edu.gr) on 2023-10-05T16:37:44Z\nNo. of bitstreams: 2\nlicense_rdf: 701 bytes, checksum: 42fd4ad1e89814f5e4a476b409eb708c (MD5)\nΜπαλκούδηΜιχαέλαMSc2023.pdf.pdf: 1189968 bytes, checksum: 093e4efbd479c424e80b1c312cfaef82 (MD5)" }, { "@language" : "en", "@value" : "In recent years, there has been an increase in awareness of mental health issues and it is widely\naccepted that their early detection is essential to preventing social consequences. The use of\nquestionnaires is a common medical technique for promptly detecting mental health concerns.\nSome scientists have proposed further automating the diagnosis of one mental condition by\nutilizing a questionnaire that diagnoses another condition. However, more research and study\nare required in order to prove the effectiveness of this further automation of the diagnosis of\nmental disorders and make it practical. This thesis investigates two questions. First whether\na standardized memory questionnaire known as the PRMQ (Prospective and Recall Memory\nQuestionnaire) along with a few demographic and general health-related questions, may be\nused to diagnose depression. Second, we try to investigate the reverse, that is whether memory-\nrelated disorders may be diagnosed in patients by using a common questionnaire that makes\na diagnosis of depression called the ZUNG Depression Questionnaire (SDS), coupled with the\nsame demographic questions and health-related questions used in the first investigation. The\nselection of these two mental illnesses is not arbitrary; rather, it is based on their usual co-\noccurrence and the link that has been found between them. Both questions will be inves-\ntigating via machine learning techniques. More specifically, question is approached in two\nways: as a regression and as a classification task. For each such task, suitable machine learn-\ning models are applied and compared in order to find the one with the best performance. The\nmemory-related classification task will turn out to be an imbalanced classification problem,\nhence appropriate methods, such as resampling during training and cost-sensitive algorithms,\nare used to resolve it. Our results show that we can diagnose depression through the memory\nquestionnaire, coupled with some demographic questions and health-related questions with an\naccuracy of approximately 79%. The diagnosis of memory-related issues via the Zung depres-\nsion questionnaire could not be achieved with adequate accuracy. This does not necessarily\nimply that we can not diagnose memory-related issues from a depression questionnaire, but\nmore research is needed to improve performance." }, { "@language" : "el", "@value" : "Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2023." } ], "identifier" : "http://dspace.lib.uom.gr/handle/2159/29441", "publisher" : { "@language" : "el", "@value" : "Πανεπιστήμιο Μακεδονίας" }, "rights" : [ { "@language" : "el", "@value" : "CC0 1.0 Παγκόσμια" }, { "@language" : "en", "@value" : "http://creativecommons.org/publicdomain/zero/1.0/" } ], "subject" : [ { "@language" : "en", "@value" : "Memory issues" }, { "@language" : "en", "@value" : "Prediction" }, { "@id" : "http://semantics.gr/authorities/EKT-voc-classifier/605963148" }, { "@language" : "en", "@value" : "Depression" } ], "title" : { "@language" : "en", "@value" : "Machine learning-based mood classification via standardized questionnaires" }, "type" : [ { "@language" : "en", "@value" : "Text" }, { "@language" : "en", "@value" : "Electronic Thesis or Dissertation" }, { "@id" : "http://semantics.gr/authorities/openarchives-item-types/metaptyxiakh-ergasia" } ], "created" : "2023-10-06T07:41:37Z" } ], "@context" : { "rights" : { "@id" : "http://purl.org/dc/elements/1.1/rights" }, "creator" : { "@id" : "http://purl.org/dc/elements/1.1/creator" }, "type" : { "@id" : "http://purl.org/dc/elements/1.1/type" }, "description" : { "@id" : "http://purl.org/dc/elements/1.1/description" }, "publisher" : { "@id" : "http://purl.org/dc/elements/1.1/publisher" }, "title" : { "@id" : "http://purl.org/dc/elements/1.1/title" }, "subject" : { "@id" : "http://purl.org/dc/elements/1.1/subject" }, "contributor" : { "@id" : "http://purl.org/dc/elements/1.1/contributor" }, "identifier" : { "@id" : "http://purl.org/dc/elements/1.1/identifier" }, "created" : { "@id" : "http://purl.org/dc/terms/created" }, "provider" : { "@id" : "http://www.europeana.eu/schemas/edm/provider" }, "isShownAt" : { "@id" : "http://www.europeana.eu/schemas/edm/isShownAt", "@type" : "@id" }, "dataProvider" : { "@id" : "http://www.europeana.eu/schemas/edm/dataProvider" }, "aggregatedCHO" : { "@id" : "http://www.europeana.eu/schemas/edm/aggregatedCHO", "@type" : "@id" }, "exactMatch" : { "@id" : "http://www.w3.org/2004/02/skos/core#exactMatch", "@type" : "@id" }, "broader" : { "@id" : "http://www.w3.org/2004/02/skos/core#broader", "@type" : "@id" }, "prefLabel" : { "@id" : "http://www.w3.org/2004/02/skos/core#prefLabel" }, "relatedMatch" : { "@id" : "http://www.w3.org/2004/02/skos/core#relatedMatch", "@type" : "@id" }, "note" : { "@id" : "http://www.w3.org/2004/02/skos/core#note" }, "closeMatch" : { "@id" : "http://www.w3.org/2004/02/skos/core#closeMatch", "@type" : "@id" }, "ore" : "http://www.openarchives.org/ore/terms/", "owl" : "http://www.w3.org/2002/07/owl#", "svcs" : "http://rdfs.org/sioc/services#", "skos" : "http://www.w3.org/2004/02/skos/core#", "rdfs" : "http://www.w3.org/2000/01/rdf-schema#", "rdaGr2" : "http://rdvocab.info/ElementsGr2/", "edm" : "http://www.europeana.eu/schemas/edm/", "ekt" : "https://www.semantics.gr/authorities/schemanamespaces/ekt#", "doap" : "http://usefulinc.com/ns/doap#", "rdf" : "http://www.w3.org/1999/02/22-rdf-syntax-ns#", "xalan" : "http://xml.apache.org/xalan", "dcterms" : "http://purl.org/dc/terms/", "wgs84_pos" : "http://www.w3.org/2003/01/geo/wgs84_pos#", "foaf" : "http://xmlns.com/foaf/0.1/", "crm" : "http://www.cidoc-crm.org/rdfs/cidoc_crm_v5.0.2_english_label.rdfs#", "dc" : "http://purl.org/dc/elements/1.1/" } }