Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study
<p dir="ltr">Identifying human diseases remains a difficult process, even in the age of advanced information technology and the smart healthcare industry 5.0. In the smart healthcare industry 5.0, precise prediction of human diseases, particularly lethal cancer diseases, is critical...
محفوظ في:
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| مؤلفون آخرون: | , , , , , , , , |
| منشور في: |
2023
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| _version_ | 1864513527889264640 |
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| author | TAHIR ABBAS KHAN (17947862) |
| author2 | AREEJ FATIMA (17947865) TARIQ SHAHZAD (17947868) ATTA-UR- RAHMAN (17947869) KHALID ALISSA (17947870) TAHER M. GHAZAL (17947872) MAHMOUD M. AL-SAKHNINI (17947874) SAGHEER ABBAS (17947875) MUHAMMAD ADNAN KHAN (17947881) ARFAN AHMED (17947884) |
| author2_role | author author author author author author author author author |
| author_facet | TAHIR ABBAS KHAN (17947862) AREEJ FATIMA (17947865) TARIQ SHAHZAD (17947868) ATTA-UR- RAHMAN (17947869) KHALID ALISSA (17947870) TAHER M. GHAZAL (17947872) MAHMOUD M. AL-SAKHNINI (17947874) SAGHEER ABBAS (17947875) MUHAMMAD ADNAN KHAN (17947881) ARFAN AHMED (17947884) |
| author_role | author |
| dc.creator.none.fl_str_mv | TAHIR ABBAS KHAN (17947862) AREEJ FATIMA (17947865) TARIQ SHAHZAD (17947868) ATTA-UR- RAHMAN (17947869) KHALID ALISSA (17947870) TAHER M. GHAZAL (17947872) MAHMOUD M. AL-SAKHNINI (17947874) SAGHEER ABBAS (17947875) MUHAMMAD ADNAN KHAN (17947881) ARFAN AHMED (17947884) |
| dc.date.none.fl_str_mv | 2023-04-10T15:00:00Z |
| dc.identifier.none.fl_str_mv | 10.57945/manara.25204250.v1 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Secure_IoMT_for_Disease_Prediction_Empowered_With_Transfer_Learning_in_Healthcare_5_0_the_Concept_and_Case_Study/25204250 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Information and computing sciences Artificial intelligence Transfer learning Medical services Diseases Training Lung cancer Internet on Medical Things Adaptation models Biomedical image processing |
| dc.title.none.fl_str_mv | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Identifying human diseases remains a difficult process, even in the age of advanced information technology and the smart healthcare industry 5.0. In the smart healthcare industry 5.0, precise prediction of human diseases, particularly lethal cancer diseases, is critical for human well-being. The global Internet of Medical Things sector has advanced at a breakneck pace in recent years, from small wristwatches to large aircraft. The critical aspects of the Internet of Medical Things include security and privacy, owing to the massive scale and deployment of the Internet of Medical Things networks. Transfer learning with a secure IoMT-based approach is considered. The Google net deep machine-learning model is used for accurate disease prediction in the smart healthcare industry 5.0. We can easily and reliably anticipate the lethal cancer disease in the human body by using the secure IoMT-based transfer learning approach. Furthermore, the results of the proposed secure IoMT-based Transfer learning techniques are used to validate the best cancer disease prediction in the smart healthcare industry 5.0. The proposed secure IoMT-based transfer learning methodology reached 98.8%, better than the state-of-the-art methodologies used previously for cancer disease prediction in the smart healthcare industry 5.0.</p><p><br></p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://doi.org/10.1109/access.2023.3266156" target="_blank">https://doi.org/10.1109/access.2023.3266156</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_b4223527db633225e9a7cc6eeb45fa08 |
| identifier_str_mv | 10.57945/manara.25204250.v1 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25204250 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case StudyTAHIR ABBAS KHAN (17947862)AREEJ FATIMA (17947865)TARIQ SHAHZAD (17947868)ATTA-UR- RAHMAN (17947869)KHALID ALISSA (17947870)TAHER M. GHAZAL (17947872)MAHMOUD M. AL-SAKHNINI (17947874)SAGHEER ABBAS (17947875)MUHAMMAD ADNAN KHAN (17947881)ARFAN AHMED (17947884)Biomedical and clinical sciencesClinical sciencesInformation and computing sciencesArtificial intelligenceTransfer learningMedical servicesDiseasesTrainingLung cancerInternet on Medical ThingsAdaptation modelsBiomedical image processing<p dir="ltr">Identifying human diseases remains a difficult process, even in the age of advanced information technology and the smart healthcare industry 5.0. In the smart healthcare industry 5.0, precise prediction of human diseases, particularly lethal cancer diseases, is critical for human well-being. The global Internet of Medical Things sector has advanced at a breakneck pace in recent years, from small wristwatches to large aircraft. The critical aspects of the Internet of Medical Things include security and privacy, owing to the massive scale and deployment of the Internet of Medical Things networks. Transfer learning with a secure IoMT-based approach is considered. The Google net deep machine-learning model is used for accurate disease prediction in the smart healthcare industry 5.0. We can easily and reliably anticipate the lethal cancer disease in the human body by using the secure IoMT-based transfer learning approach. Furthermore, the results of the proposed secure IoMT-based Transfer learning techniques are used to validate the best cancer disease prediction in the smart healthcare industry 5.0. The proposed secure IoMT-based transfer learning methodology reached 98.8%, better than the state-of-the-art methodologies used previously for cancer disease prediction in the smart healthcare industry 5.0.</p><p><br></p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://doi.org/10.1109/access.2023.3266156" target="_blank">https://doi.org/10.1109/access.2023.3266156</a></p>2023-04-10T15:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.57945/manara.25204250.v1https://figshare.com/articles/journal_contribution/Secure_IoMT_for_Disease_Prediction_Empowered_With_Transfer_Learning_in_Healthcare_5_0_the_Concept_and_Case_Study/25204250CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/252042502023-04-10T15:00:00Z |
| spellingShingle | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study TAHIR ABBAS KHAN (17947862) Biomedical and clinical sciences Clinical sciences Information and computing sciences Artificial intelligence Transfer learning Medical services Diseases Training Lung cancer Internet on Medical Things Adaptation models Biomedical image processing |
| status_str | publishedVersion |
| title | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| title_full | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| title_fullStr | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| title_full_unstemmed | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| title_short | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| title_sort | Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study |
| topic | Biomedical and clinical sciences Clinical sciences Information and computing sciences Artificial intelligence Transfer learning Medical services Diseases Training Lung cancer Internet on Medical Things Adaptation models Biomedical image processing |