Design and implementation of a deep learning-empowered m-Health application
<p dir="ltr">Many people are unaware of the severity of melanoma disease even though such a disease can be fatal if not treated early. This research aims to facilitate the diagnosis of melanoma disease in people using a mobile health application because some people do not prefer to v...
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2023
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| _version_ | 1864513530901823488 |
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| author | Akhan Akbulut (17380285) |
| author2 | Sara Desouki (17785661) Sara AbdelKhaliq (17785664) Layal Khantomani (17785667) Cagatay Catal (6897842) |
| author2_role | author author author author |
| author_facet | Akhan Akbulut (17380285) Sara Desouki (17785661) Sara AbdelKhaliq (17785664) Layal Khantomani (17785667) Cagatay Catal (6897842) |
| author_role | author |
| dc.creator.none.fl_str_mv | Akhan Akbulut (17380285) Sara Desouki (17785661) Sara AbdelKhaliq (17785664) Layal Khantomani (17785667) Cagatay Catal (6897842) |
| dc.date.none.fl_str_mv | 2023-09-28T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1007/s11042-023-17041-x |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Design_and_implementation_of_a_deep_learning-empowered_m-Health_application/24995708 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Health services and systems Information and computing sciences Machine learning Melanoma Machine learning Deep learning m-Health Skin lesion analysis |
| dc.title.none.fl_str_mv | Design and implementation of a deep learning-empowered m-Health application |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Many people are unaware of the severity of melanoma disease even though such a disease can be fatal if not treated early. This research aims to facilitate the diagnosis of melanoma disease in people using a mobile health application because some people do not prefer to visit a dermatologist due to several concerns such as feeling uncomfortable by exposing their bodies. As such, a skincare application was developed so that a user can easily analyze a mole at any part of the body and get the diagnosis results quickly. In the first phase, the corresponding image is extracted and sent to a web service. Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. The final phase displays the confidence rates on the mobile application. The proposed model utilizes the Convolutional Neural Network and provides 84% accuracy and 72% precision. The results demonstrate that the proposed model and the corresponding mobile application provide remarkable results for addressing the specified health problem.</p><h2>Other Information</h2><p dir="ltr">Published in: Multimedia Tools and Applications<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s11042-023-17041-x" target="_blank">https://dx.doi.org/10.1007/s11042-023-17041-x</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_c84ce9ece130dba1fd37fe2e3241eea9 |
| identifier_str_mv | 10.1007/s11042-023-17041-x |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24995708 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Design and implementation of a deep learning-empowered m-Health applicationAkhan Akbulut (17380285)Sara Desouki (17785661)Sara AbdelKhaliq (17785664)Layal Khantomani (17785667)Cagatay Catal (6897842)Health sciencesHealth services and systemsInformation and computing sciencesMachine learningMelanomaMachine learningDeep learningm-HealthSkin lesion analysis<p dir="ltr">Many people are unaware of the severity of melanoma disease even though such a disease can be fatal if not treated early. This research aims to facilitate the diagnosis of melanoma disease in people using a mobile health application because some people do not prefer to visit a dermatologist due to several concerns such as feeling uncomfortable by exposing their bodies. As such, a skincare application was developed so that a user can easily analyze a mole at any part of the body and get the diagnosis results quickly. In the first phase, the corresponding image is extracted and sent to a web service. Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. The final phase displays the confidence rates on the mobile application. The proposed model utilizes the Convolutional Neural Network and provides 84% accuracy and 72% precision. The results demonstrate that the proposed model and the corresponding mobile application provide remarkable results for addressing the specified health problem.</p><h2>Other Information</h2><p dir="ltr">Published in: Multimedia Tools and Applications<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s11042-023-17041-x" target="_blank">https://dx.doi.org/10.1007/s11042-023-17041-x</a></p>2023-09-28T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s11042-023-17041-xhttps://figshare.com/articles/journal_contribution/Design_and_implementation_of_a_deep_learning-empowered_m-Health_application/24995708CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/249957082023-09-28T03:00:00Z |
| spellingShingle | Design and implementation of a deep learning-empowered m-Health application Akhan Akbulut (17380285) Health sciences Health services and systems Information and computing sciences Machine learning Melanoma Machine learning Deep learning m-Health Skin lesion analysis |
| status_str | publishedVersion |
| title | Design and implementation of a deep learning-empowered m-Health application |
| title_full | Design and implementation of a deep learning-empowered m-Health application |
| title_fullStr | Design and implementation of a deep learning-empowered m-Health application |
| title_full_unstemmed | Design and implementation of a deep learning-empowered m-Health application |
| title_short | Design and implementation of a deep learning-empowered m-Health application |
| title_sort | Design and implementation of a deep learning-empowered m-Health application |
| topic | Health sciences Health services and systems Information and computing sciences Machine learning Melanoma Machine learning Deep learning m-Health Skin lesion analysis |