Matches in SemOpenAlex for { <https://semopenalex.org/work/W2964208452> ?p ?o ?g. }
- W2964208452 abstract "Mood disorders are common and associated with significant morbidity and mortality. Early diagnosis has the potential to greatly alleviate the burden of mental illness and the ever increasing costs to families and society. Mobile devices provide us a promising opportunity to detect the users' mood in an unobtrusive manner. In this study, we use a custom keyboard which collects keystrokes' meta-data and accelerometer values. Based on the collected time series data in multiple modalities, we propose a deep personalized mood prediction approach, called dpMood, by integrating convolutional and recurrent deep architectures as well as exploring each individual's circadian rhythm. Experimental results not only demonstrate the feasibility and effectiveness of using smart-phone meta-data to predict the presence and severity of mood disturbances in bipolar subjects, but also show the potential of personalized medical treatment for mood disorders." @default.
- W2964208452 created "2019-07-30" @default.
- W2964208452 creator A5002457406 @default.
- W2964208452 creator A5035692604 @default.
- W2964208452 creator A5062156254 @default.
- W2964208452 creator A5076335744 @default.
- W2964208452 creator A5089773619 @default.
- W2964208452 date "2018-11-01" @default.
- W2964208452 modified "2023-09-30" @default.
- W2964208452 title "dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction" @default.
- W2964208452 cites W1767492358 @default.
- W2964208452 cites W1832693441 @default.
- W2964208452 cites W1853995153 @default.
- W2964208452 cites W1894490285 @default.
- W2964208452 cites W1906543112 @default.
- W2964208452 cites W1966554111 @default.
- W2964208452 cites W1977831800 @default.
- W2964208452 cites W1991022130 @default.
- W2964208452 cites W1997102766 @default.
- W2964208452 cites W2008803468 @default.
- W2964208452 cites W2016202965 @default.
- W2964208452 cites W2029438113 @default.
- W2964208452 cites W2039260438 @default.
- W2964208452 cites W2049877533 @default.
- W2964208452 cites W2052331661 @default.
- W2964208452 cites W2064675550 @default.
- W2964208452 cites W2065864529 @default.
- W2964208452 cites W2084959893 @default.
- W2964208452 cites W2086173258 @default.
- W2964208452 cites W2088616391 @default.
- W2964208452 cites W2098759488 @default.
- W2964208452 cites W2115298650 @default.
- W2964208452 cites W2118826874 @default.
- W2964208452 cites W2120615054 @default.
- W2964208452 cites W2127941101 @default.
- W2964208452 cites W2144279833 @default.
- W2964208452 cites W2157331557 @default.
- W2964208452 cites W2157877920 @default.
- W2964208452 cites W2167636534 @default.
- W2964208452 cites W2167659819 @default.
- W2964208452 cites W2266871031 @default.
- W2964208452 cites W2321609854 @default.
- W2964208452 cites W2539690336 @default.
- W2964208452 cites W2582919740 @default.
- W2964208452 cites W2605108175 @default.
- W2964208452 cites W2744939564 @default.
- W2964208452 cites W3123876770 @default.
- W2964208452 cites W4231686096 @default.
- W2964208452 cites W4243744905 @default.
- W2964208452 cites W58346954 @default.
- W2964208452 doi "https://doi.org/10.1109/icdm.2018.00031" @default.
- W2964208452 hasPublicationYear "2018" @default.
- W2964208452 type Work @default.
- W2964208452 sameAs 2964208452 @default.
- W2964208452 citedByCount "16" @default.
- W2964208452 countsByYear W29642084522019 @default.
- W2964208452 countsByYear W29642084522020 @default.
- W2964208452 countsByYear W29642084522021 @default.
- W2964208452 countsByYear W29642084522022 @default.
- W2964208452 countsByYear W29642084522023 @default.
- W2964208452 crossrefType "proceedings-article" @default.
- W2964208452 hasAuthorship W2964208452A5002457406 @default.
- W2964208452 hasAuthorship W2964208452A5035692604 @default.
- W2964208452 hasAuthorship W2964208452A5062156254 @default.
- W2964208452 hasAuthorship W2964208452A5076335744 @default.
- W2964208452 hasAuthorship W2964208452A5089773619 @default.
- W2964208452 hasBestOaLocation W29642084522 @default.
- W2964208452 hasConcept C118552586 @default.
- W2964208452 hasConcept C119857082 @default.
- W2964208452 hasConcept C144024400 @default.
- W2964208452 hasConcept C154945302 @default.
- W2964208452 hasConcept C2777134132 @default.
- W2964208452 hasConcept C2779903281 @default.
- W2964208452 hasConcept C2780733359 @default.
- W2964208452 hasConcept C36289849 @default.
- W2964208452 hasConcept C41008148 @default.
- W2964208452 hasConcept C558461103 @default.
- W2964208452 hasConcept C71924100 @default.
- W2964208452 hasConceptScore W2964208452C118552586 @default.
- W2964208452 hasConceptScore W2964208452C119857082 @default.
- W2964208452 hasConceptScore W2964208452C144024400 @default.
- W2964208452 hasConceptScore W2964208452C154945302 @default.
- W2964208452 hasConceptScore W2964208452C2777134132 @default.
- W2964208452 hasConceptScore W2964208452C2779903281 @default.
- W2964208452 hasConceptScore W2964208452C2780733359 @default.
- W2964208452 hasConceptScore W2964208452C36289849 @default.
- W2964208452 hasConceptScore W2964208452C41008148 @default.
- W2964208452 hasConceptScore W2964208452C558461103 @default.
- W2964208452 hasConceptScore W2964208452C71924100 @default.
- W2964208452 hasLocation W29642084521 @default.
- W2964208452 hasLocation W29642084522 @default.
- W2964208452 hasOpenAccess W2964208452 @default.
- W2964208452 hasPrimaryLocation W29642084521 @default.
- W2964208452 hasRelatedWork W2961085424 @default.
- W2964208452 hasRelatedWork W3046775127 @default.
- W2964208452 hasRelatedWork W3170094116 @default.
- W2964208452 hasRelatedWork W4205958290 @default.
- W2964208452 hasRelatedWork W4285260836 @default.
- W2964208452 hasRelatedWork W4286629047 @default.
- W2964208452 hasRelatedWork W4306321456 @default.