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dc.contributor.authorTürker, Mehmet Nasuhcan
dc.contributor.authorÇagan, Yagiz Can
dc.contributor.authorYıldırım, Batuhan
dc.contributor.authorDemirel, Mücahit
dc.contributor.authorÖzmen, Atilla
dc.contributor.authorTander, Baran
dc.contributor.authorÇevik, Mesut
dc.date.accessioned2021-01-28T09:34:43Z
dc.date.available2021-01-28T09:34:43Z
dc.date.issued2020
dc.identifier.isbn978-172818073-1
dc.identifier.urihttps://doi.org/10.1109/TIPTEKNO50054.2020.9299229en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/3757
dc.description.abstractIn this study, a device named smart stethoscope that uses digital sensor technology for sound capture, active acoustics for noise cancellation and artificial intelligence (AI) for diagnosis of heart and lung diseases is developed to help the health workers to make accurate diagnoses. Furthermore, the respiratory diseases are classified by using Deep Learning and Long Short-Term Memory (LSTM) techniques whereas the probability of these diseases are obtained.en_US
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectAmplifiersen_US
dc.subjectDeep learningen_US
dc.subjectDiagnosisen_US
dc.subjectFiltersen_US
dc.subjectHeart and lung soundsen_US
dc.subjectLong short-term memoryen_US
dc.subjectStethoscopeen_US
dc.titleSmart Stethoscopeen_US
dc.typeConference Proceedingen_US
dc.relation.journal2020 Medical Technologies Congressen_US
dc.identifier.doi10.1109/TIPTEKNO50054.2020.9299229en_US
dc.contributor.khasauthorÇevik, Mesuten_US
dc.contributor.khasauthorTander, Baranen_US
dc.contributor.khasauthorÖzmen, Atillaen_US
dc.contributor.khasauthorDemirel, Mücahiten_US
dc.contributor.khasauthorYıldırım, Batuhanen_US
dc.contributor.khasauthorÇagan, Yagiz Canen_US
dc.contributor.khasauthorTürker, Mehmet Nasuhcanen_US


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