Smart Stethoscope
| dc.contributor.author | Türker, Mehmet Nasuhcan | |
| dc.contributor.author | Çevik, Mesut | |
| dc.contributor.author | Çagan, Yagiz Can | |
| dc.contributor.author | Özmen, Atilla | |
| dc.contributor.author | Yıldırım, Batuhan | |
| dc.contributor.author | Tander, Baran | |
| dc.contributor.author | Demirel, Mücahit | |
| dc.contributor.author | Özmen, Atilla | |
| dc.contributor.author | Tander, Baran | |
| dc.contributor.author | Çevik, Mesut | |
| dc.contributor.other | Computer Engineering | |
| dc.contributor.other | Electrical-Electronics Engineering | |
| dc.date.accessioned | 2021-01-28T09:34:43Z | |
| dc.date.available | 2021-01-28T09:34:43Z | |
| dc.date.issued | 2020 | |
| dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
| dc.description.abstract | In 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.identifier.citationcount | 0 | |
| dc.identifier.doi | 10.1109/TIPTEKNO50054.2020.9299229 | en_US |
| dc.identifier.isbn | 978-172818073-1 | |
| dc.identifier.scopus | 2-s2.0-85099450861 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/3757 | |
| dc.identifier.uri | https://doi.org/10.1109/TIPTEKNO50054.2020.9299229 | |
| dc.identifier.wos | WOS:000659419900017 | en_US |
| dc.institutionauthor | Çevik, Mesut | en_US |
| dc.institutionauthor | Tander, Baran | en_US |
| dc.institutionauthor | Özmen, Atilla | en_US |
| dc.institutionauthor | Demirel, Mücahit | en_US |
| dc.institutionauthor | Yıldırım, Batuhan | en_US |
| dc.institutionauthor | Çagan, Yagiz Can | en_US |
| dc.institutionauthor | Türker, Mehmet Nasuhcan | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.journal | 2020 Medical Technologies Congress | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/embargoedAccess | en_US |
| dc.scopus.citedbyCount | 3 | |
| dc.subject | Amplifiers | en_US |
| dc.subject | Deep learning | en_US |
| dc.subject | Diagnosis | en_US |
| dc.subject | Filters | en_US |
| dc.subject | Heart and lung sounds | en_US |
| dc.subject | Long short-term memory | en_US |
| dc.subject | Stethoscope | en_US |
| dc.title | Smart Stethoscope | en_US |
| dc.type | Conference Object | en_US |
| dc.wos.citedbyCount | 0 | |
| dspace.entity.type | Publication | |
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