Enhancing Brain Tumour Multi-Classification Using Efficient-Net B0-Based Intelligent Diagnosis for Internet of Medical Things (IoMT) Applications
Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most currently available examination methods are laborious, require extensive manual instructions, and produce subpar findings. The EfficientNet-B0 arch...
Saved in:
| Published in: | Information (Basel) Vol. 15; no. 8; p. 489 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Basel
MDPI AG
01.08.2024
|
| Subjects: | |
| ISSN: | 2078-2489, 2078-2489 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most currently available examination methods are laborious, require extensive manual instructions, and produce subpar findings. The EfficientNet-B0 architecture was used to diagnose brain tumours using magnetic resonance imaging (MRI). The fine-tuned EffeceintNet B0 model was proposed for the Internet of Medical Things (IoMT) environment. The fine-tuned EfficientNet-B0 architecture was employed to classify four different stages of brain tumours from the MRI images. The fine-tuned model showed 99% accuracy in the detection of four different classes of brain tumour detection (glioma, no tumour, meningioma, and pituitary). The proposed model performed very well in the detection of the pituitary class with a precision of 0.95, recall of 0.98, and F1 score of 0.96. The proposed model also performed very well in the detection of the no-tumour class with values of 0.99, 0.90, and 0.94 for precision, recall, and the F1 score, respectively. The precision, recall, and F1 scores for Glioma and Meningioma classes were also high. The proposed solution has several implications for enhancing clinical investigations of brain tumours. |
|---|---|
| AbstractList | Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most currently available examination methods are laborious, require extensive manual instructions, and produce subpar findings. The EfficientNet-B0 architecture was used to diagnose brain tumours using magnetic resonance imaging (MRI). The fine-tuned EffeceintNet B0 model was proposed for the Internet of Medical Things (IoMT) environment. The fine-tuned EfficientNet-B0 architecture was employed to classify four different stages of brain tumours from the MRI images. The fine-tuned model showed 99% accuracy in the detection of four different classes of brain tumour detection (glioma, no tumour, meningioma, and pituitary). The proposed model performed very well in the detection of the pituitary class with a precision of 0.95, recall of 0.98, and F1 score of 0.96. The proposed model also performed very well in the detection of the no-tumour class with values of 0.99, 0.90, and 0.94 for precision, recall, and the F1 score, respectively. The precision, recall, and F1 scores for Glioma and Meningioma classes were also high. The proposed solution has several implications for enhancing clinical investigations of brain tumours. |
| Author | Jaffar, Muhammad Arfan Iqbal, Amna Jahangir, Rashid |
| Author_xml | – sequence: 1 givenname: Amna surname: Iqbal fullname: Iqbal, Amna – sequence: 2 givenname: Muhammad Arfan surname: Jaffar fullname: Jaffar, Muhammad Arfan – sequence: 3 givenname: Rashid orcidid: 0000-0003-1129-6006 surname: Jahangir fullname: Jahangir, Rashid |
| BookMark | eNptUU1vEzEQtVCRKKU3foAlLiCxMP7I2j42IS2RGrikZ8v2elNHWzvYzqE_g3-MmxSpQsxlRm_ePI_fvEVnMUWP0HsCXxhT8DXEMZEZSOBSvULnFITsaKvPXtRv0GUpO2ghhOSSnKPfy3hvogtxi-fZhIg3h4d0yHh9mGroFpMpJYzBmRpSxHflibccGxB8rN0PX_EcurkpfsCrWP00hW1r4G_BbGMqoeAx5WMnx8ZNI177oalNeHPfpAr-uErrzSd8td9Pz4-Ud-j1aKbiL5_zBbq7Xm4W37vbnzerxdVt51gvajdYMfTSet9zbhVwLjl1woAC31ywFphgijBllTRKUdEAMKN0HGwPhPbsAq1OukMyO73P4cHkR51M0Ecg5a02uQY3ee2lMnbmBFhqOfHMMs8YBSpHIo23oml9OGntc_p18KXqXTMxtvU1AyUUJQRmjUVPLJdTKdmP2oV6_HRt1k-agH66pH55yTb0-Z-hv6v-l_4HRl-hYA |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2024_3524732 crossref_primary_10_1007_s44174_025_00468_1 |
| Cites_doi | 10.1016/j.compmedimag.2019.05.001 10.1007/s12652-020-02568-w 10.1109/JSTQE.2019.2950795 10.1016/j.cmpb.2021.106597 10.1016/j.neucom.2022.07.005 10.1016/j.compeleceng.2022.108196 10.1109/MAJICC53071.2021.9526262 10.1002/cpe.6541 10.1002/ima.22554 10.1016/j.comnet.2019.04.016 10.1088/1757-899X/1055/1/012115 10.1016/j.bspc.2023.104777 10.1109/ACCESS.2018.2880838 10.1007/s11042-022-12977-y 10.1109/ICCES51350.2021.9489187 10.1007/s11760-020-01793-2 10.20473/jisebi.9.1.1-15 10.1016/j.comcom.2020.11.013 10.3390/jpm13020181 10.3390/healthcare9020153 10.32604/csse.2023.024674 10.1101/2022.07.18.22277779 10.3390/cancers15102837 10.1093/neuros/nyy543 10.32604/cmc.2022.029000 10.3390/electronics12040955 |
| ContentType | Journal Article |
| Copyright | 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | AAYXX CITATION 3V. 7SC 7XB 8AL 8FD 8FE 8FG 8FK ABUWG AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ JQ2 K7- L7M L~C L~D M0N P5Z P62 PHGZM PHGZT PIMPY PKEHL PQEST PQGLB PQQKQ PQUKI PRINS Q9U DOA |
| DOI | 10.3390/info15080489 |
| DatabaseName | CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts ProQuest Central (purchase pre-March 2016) Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Technology collection ProQuest One Community College ProQuest Central ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Computing Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef Publicly Available Content Database Computer Science Database ProQuest Central Student Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Central Korea ProQuest Central (New) Advanced Technologies Database with Aerospace Advanced Technologies & Aerospace Collection ProQuest Computing ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest SciTech Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) |
| DatabaseTitleList | CrossRef Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 2078-2489 |
| ExternalDocumentID | oai_doaj_org_article_e89ab5c70b2b41e3b3e332028f18aeb7 10_3390_info15080489 |
| GroupedDBID | .4I 5VS 8FE 8FG AADQD AAFWJ AAYXX ABDBF ABUWG ADBBV ADMLS AFFHD AFKRA AFPKN AFZYC ALMA_UNASSIGNED_HOLDINGS ARAPS AZQEC BCNDV BENPR BGLVJ BPHCQ CCPQU CITATION DWQXO GNUQQ GROUPED_DOAJ HCIFZ IAO ITC K6V K7- KQ8 MK~ ML~ MODMG M~E OK1 P2P P62 PHGZM PHGZT PIMPY PQGLB PQQKQ PROAC XH6 3V. 7SC 7XB 8AL 8FD 8FK JQ2 L7M L~C L~D M0N PKEHL PQEST PQUKI PRINS Q9U |
| ID | FETCH-LOGICAL-c367t-db7d68bee644b9044842c7a090e150bb03739139b98a9927b030af8c40b601263 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 3 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001304788500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2078-2489 |
| IngestDate | Mon Nov 10 04:34:49 EST 2025 Sat Jul 26 00:23:32 EDT 2025 Tue Nov 18 19:44:47 EST 2025 Sat Nov 29 07:18:01 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 8 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c367t-db7d68bee644b9044842c7a090e150bb03739139b98a9927b030af8c40b601263 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0003-1129-6006 |
| OpenAccessLink | https://doaj.org/article/e89ab5c70b2b41e3b3e332028f18aeb7 |
| PQID | 3097921105 |
| PQPubID | 2032384 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_e89ab5c70b2b41e3b3e332028f18aeb7 proquest_journals_3097921105 crossref_citationtrail_10_3390_info15080489 crossref_primary_10_3390_info15080489 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-08-01 |
| PublicationDateYYYYMMDD | 2024-08-01 |
| PublicationDate_xml | – month: 08 year: 2024 text: 2024-08-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Basel |
| PublicationPlace_xml | – name: Basel |
| PublicationTitle | Information (Basel) |
| PublicationYear | 2024 |
| Publisher | MDPI AG |
| Publisher_xml | – name: MDPI AG |
| References | Graber (ref_2) 2019; 84 Meera (ref_10) 2018; 5 ref_14 Isunuri (ref_21) 2022; 34 ref_12 ref_11 ref_31 ref_30 ref_18 Deepak (ref_22) 2021; 12 Kamil (ref_24) 2021; 11 Din (ref_7) 2018; 7 Swati (ref_3) 2019; 75 Kakarla (ref_16) 2021; 31 Elhoseny (ref_6) 2019; 159 Li (ref_1) 2019; 25 Ganesan (ref_17) 2020; 16 Huang (ref_8) 2022; 504 Kibriya (ref_19) 2022; 81 ref_20 Brindha (ref_15) 2021; Volume 1055 Bodapati (ref_4) 2021; 15 ref_29 ref_28 Gao (ref_13) 2021; 166 ref_27 ref_26 ref_9 Vankdothu (ref_23) 2022; 102 ref_5 Rajathi (ref_25) 2023; 44 |
| References_xml | – ident: ref_28 – volume: 75 start-page: 34 year: 2019 ident: ref_3 article-title: Brain tumor classification for MR images using transfer learning and fine-tuning publication-title: Comput. Med Imaging Graph. doi: 10.1016/j.compmedimag.2019.05.001 – volume: 12 start-page: 8357 year: 2021 ident: ref_22 article-title: Automated categorization of brain tumor from mri using cnn features and svm publication-title: J. Ambient Intell. Humaniz. Comput. doi: 10.1007/s12652-020-02568-w – ident: ref_5 – volume: 5 start-page: e17 year: 2018 ident: ref_10 article-title: A review on automatic detection of brain tumor using computer aided diagnosis system through MRI publication-title: EAI Endorsed Trans. Energy Web – volume: 25 start-page: 1 year: 2019 ident: ref_1 article-title: Polarization-sensitive optical coherence tomography for brain tumor characterization publication-title: IEEE J. Sel. Top. Quantum Electron. doi: 10.1109/JSTQE.2019.2950795 – ident: ref_20 doi: 10.1016/j.cmpb.2021.106597 – volume: 504 start-page: 223 year: 2022 ident: ref_8 article-title: Applicable artificial intelligence for brain disease: A survey publication-title: Neurocomputing doi: 10.1016/j.neucom.2022.07.005 – volume: 102 start-page: 108196 year: 2022 ident: ref_23 article-title: Brain image identification and classification on Internet of Medical Things in healthcare system using support value based deep neural network publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2022.108196 – ident: ref_18 doi: 10.1109/MAJICC53071.2021.9526262 – volume: 34 start-page: e6541 year: 2022 ident: ref_21 article-title: Three-class brain tumor classification from magnetic resonance images using separable convolution based neural network publication-title: Concurr. Comput. Pract. Exp. doi: 10.1002/cpe.6541 – volume: 31 start-page: 1731 year: 2021 ident: ref_16 article-title: Three-class classification of brain magnetic resonance images using average-pooling convolutional neural network publication-title: Int. J. Imaging Syst. Technol. doi: 10.1002/ima.22554 – volume: 159 start-page: 147 year: 2019 ident: ref_6 article-title: Effective features to classify ovarian cancer data in internet of medical things publication-title: Comput. Networks doi: 10.1016/j.comnet.2019.04.016 – volume: Volume 1055 start-page: 012115 year: 2021 ident: ref_15 article-title: Brain tumor detection from MRI images using deep learning techniques publication-title: Proceedings of the IOP Conference Series: Materials Science and Engineering doi: 10.1088/1757-899X/1055/1/012115 – ident: ref_11 doi: 10.1016/j.bspc.2023.104777 – volume: 7 start-page: 29763 year: 2018 ident: ref_7 article-title: Trust management techniques for the Internet of Things: A survey publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2880838 – volume: 81 start-page: 29847 year: 2022 ident: ref_19 article-title: Multiclass classification of brain tumors using a novel CNN architecture publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12977-y – ident: ref_31 doi: 10.1109/ICCES51350.2021.9489187 – volume: 15 start-page: 753 year: 2021 ident: ref_4 article-title: Joint training of two-channel deep neural network for brain tumor classification publication-title: Signal Image Video Process. doi: 10.1007/s11760-020-01793-2 – ident: ref_27 doi: 10.20473/jisebi.9.1.1-15 – volume: 166 start-page: 57 year: 2021 ident: ref_13 article-title: Class consistent and joint group sparse representation model for image classification in internet of medical things publication-title: Comput. Commun. doi: 10.1016/j.comcom.2020.11.013 – ident: ref_26 doi: 10.3390/jpm13020181 – ident: ref_14 doi: 10.3390/healthcare9020153 – volume: 44 start-page: 1793 year: 2023 ident: ref_25 article-title: Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model publication-title: Comput. Syst. Sci. Eng. doi: 10.32604/csse.2023.024674 – ident: ref_29 doi: 10.1101/2022.07.18.22277779 – ident: ref_9 doi: 10.3390/cancers15102837 – volume: 84 start-page: E168 year: 2019 ident: ref_2 article-title: Congress of neurological surgeons systematic review and evidence-based guidelines on the use of stereotactic radiosurgery in the treatment of adults with metastatic brain tumors publication-title: Neurosurgery doi: 10.1093/neuros/nyy543 – volume: 11 start-page: 32 year: 2021 ident: ref_24 article-title: IoT framework for brain tumor classification using optimized CNN-MRFO model publication-title: Am. J. Bioinform. Res. – volume: 16 start-page: 69 year: 2020 ident: ref_17 article-title: Internet of medical things with cloud-based e-health services for brain tumour detection model using deep convolution neural network publication-title: Electron. Gov. Int. J. – ident: ref_12 doi: 10.32604/cmc.2022.029000 – ident: ref_30 doi: 10.3390/electronics12040955 |
| SSID | ssj0000778481 |
| Score | 2.307806 |
| Snippet | Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most... |
| SourceID | doaj proquest crossref |
| SourceType | Open Website Aggregation Database Enrichment Source Index Database |
| StartPage | 489 |
| SubjectTerms | Accuracy Brain Brain cancer Brain research brain tumour Cerebrospinal fluid Classification Disease EfficientNet Glioma Human error Identification Internet Internet of medical things Internet of Medical Things (IoMT) Literature reviews Machine learning Magnetic resonance imaging magnetic resonance imaging (MRI) Medical equipment Metastasis Methods multi-classification Neural networks Recall Teaching methods Tomography Tumors |
| SummonAdditionalLinks | – databaseName: Computer Science Database dbid: K7- link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3BTtwwELVaygEOUCgVW6DyoZVAyMKJzdo-VSxdVFSx6mGRuEW241AklMBu4D_448443u2iCi69JqMoyow988aT9wj5oqCul6U2AHLKwKRxhmnvM1aVXufGwvLLbBSbUKORvroyv1LDbZrGKmd7Ytyoy8Zjj_xIcKMMopXjb3f3DFWj8HQ1SWi8Je-yPM8wzn8qNu-xcKWQLb6bdxeA7o_Qa8iADnFrnmWiSNj_z34ck8zZ-v--3nuylspLetLFwwZ5E-pNsrpAOviBPA3r30iyUV_TAepD0PEDwP8Jjb_isiiSieND0WM0ThTQYeSZgPTERqGlA84GkPtKej6n82zp925k72ZKoQqmXZ8RbJuKpqMg2imE0v3z5mJ8QE8WDs63yOXZcHz6gyVhBuZFX7WsdKrsaxcCFFPOcEB4MvfKcsMDfFznuFAC6Uad0daYXMEFbivtJXeA__K--EiW6qYO24QGY4OXSkChZaUNlXXIEKgqK8BU57JHDmdOKnxiLUfxjNsC0Au6tFh0aY98nVvfdWwdL9gN0N9zG-TYjheayXWRlmwRtLHu2CvuciezIJwIAtXmdZVpG5zqkd1ZKBRp4U-Lv3Hw6fXbO2QFniW7WcJdstROHsIeWfaP7c108jnG8R-Tqfzx priority: 102 providerName: ProQuest |
| Title | Enhancing Brain Tumour Multi-Classification Using Efficient-Net B0-Based Intelligent Diagnosis for Internet of Medical Things (IoMT) Applications |
| URI | https://www.proquest.com/docview/3097921105 https://doaj.org/article/e89ab5c70b2b41e3b3e332028f18aeb7 |
| Volume | 15 |
| WOSCitedRecordID | wos001304788500001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: DOA dateStart: 20100101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: M~E dateStart: 20100101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: P5Z dateStart: 20100301 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: K7- dateStart: 20100301 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: BENPR dateStart: 20100301 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2078-2489 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000778481 issn: 2078-2489 databaseCode: PIMPY dateStart: 20100301 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1La9wwEBYhySE9hDQPsnmhQwstRURraVfSMU4cuoRdTNhC2ouRZDkJBG_YdXLMf8g_zkhyFpdSeulFYHvAZmakmbFG34fQJwF5PS-lgiKndIQro4i0tk-q0spEaZh-fR3IJsRkIm9uVN6h-vI9YREeOCru1EmlzcAKahLD-44Z5pjn_JZVX2pnwjlyyHo6xVRYg4XwOPGx051BXX_q7eWxz8Fj1W8xKED1_7ESh_ByuYU227wQn8Xv-YhWXL2NPnTQAnfQa1bfeXSM-hanntgBT5-gbp_jcIaWBHZL3_cTVI1DKwDOAkAExBUycQ1OKUkhaJV4tMThbPBF7LW7X2BIX3H8QQiyswq3ezg4UnviL6PZePoVn3V2vHfRj8tsev6dtIwKxLKhaEhpRDmUxjnIgoyiUJrxxApNFXWgG2MoE8zjhBoltVKJgBtUV9JyaqBwS4ZsD63Ws9rtI-yUdpYLBhmS5tpV2nhoP1FpBqIy4T307V3HhW3hxj3rxUMBZYe3SNG1SA99Xko_RpiNv8il3lxLGQ-OHW6AyxStyxT_cpkeOno3dtHO2EXBqBLKV8ODg__xjkO0AVc8tgoeodVm_uSO0bp9bu4X8xO0lmaT_PokOC2MV4LAOH7JYMwHv-B5PhrnP98A86T13w |
| linkProvider | Directory of Open Access Journals |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VggQc-EYsFPCBSiBk1Wt71_YBoS7dqqu2qx4WqeISbMcplSApuymIn8Ef4TcydpJlEYJbD1yTiQ_Om_GMPX4P4JnCvF7m2mCRkwcqjTNUe9-nRe41Nxbdr2-T2ISaTvXxsTlagx_dXZjYVtnFxBSo88rHPfItwYwysVoZvD77TKNqVDxd7SQ0Gljsh29fsWRbvJrs4P_d5Hx3PHuzR1tVAerFUNU0dyofahcCZgLOMCxPJPfKMsMCJkfOMaFE5Mp0RltjuMIHzBbaS-aweOFDgeNegstSYrGE_nM0eLfc02FKRXb6pr9eCMO2Ikoi4zr6iflt5UsCAX_E_7So7d7836bjFtxo02ey3eD9NqyF8g5cXyFVvAvfx-WHSCJSnpBR1L8gs_NP-BlJV41pEgGN7VEJkSR1TJBx4tHA5ZdOQ01GjI5wbc_JZElXWpOdpiXxdEEwyyfNPiraVgVpj7pIo4BKnk-qw9kLsr3SGHAP3l7InNyH9bIqwwMgwdjgpRKYSFppQ2FdZEBUhRVoqrnswcsOFJlvWdmjOMjHDKuzCKFsFUI92FxanzVsJH-xG0V8LW0ih3h6UM1PsjYkZUEb6wZeMced7AfhRBCCY75Z9LUNTvVgo4Ne1ga2RfYLdw___fopXN2bHR5kB5Pp_iO4huPKpm9yA9br-Xl4DFf8l_p0MX-SfIjA-4tG6U8X_1cZ |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1NbxMxEB2VghAc-EYECvhAJRCy4tib2D4g1JBERIUohyBVXLa211sqtbsl2YL4Gfwdfh1j724IQnDrgevurA_eN54Ze_wewDOJeX2SKY1FTuZpoq2myrkezTOnuDbofj0TxSbkbKYODvR8C360d2FCW2W7JsaFOitd2CPvCqalDtVKv5s3bRHz0eT12WcaFKTCSWsrp1FDZN9_-4rl2-rVdIT_epfzyXjx5i1tFAaoEwNZ0czKbKCs95gVWM2wVEm4k4Zp5jFRspYJKQJvptXKaM0lPmAmVy5hFgsZPhA47iW4LLHGDIXfvP9xvb_DpAxM9XWvvRCadQNiAvs6-oz-LQpGsYA_YkEMcJOb__PU3IIbTVpN9mo_uA1bvrgD1zfIFu_C93HxKZCLFEdkGHQxyOL8FD8j8QoyjeKgoW0qIpXETgoyjvwaGJbpzFdkyOgQY35Gpmsa04qM6lbF4xXB7J_U-6toW-akOQIjtTIqeT4t3y9ekL2NhoF78OFC5uQ-bBdl4R8A8dp4l0iBCaZJjM-NDcyIMjcCTRVPOvCyBUjqGrb2IBpykmLVFuCUbsKpA7tr67OapeQvdsOAtbVN4BaPD8rlUdosValX2ti-k8xym_S8sMILwTEPzXvKeCs7sNPCMG0WvFX6C4MP__36KVxFcKbvprP9R3ANh03qdsod2K6W5_4xXHFfquPV8kl0JwKHFw3SnxFwX-0 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Enhancing+Brain+Tumour+Multi-Classification+Using+Efficient-Net+B0-Based+Intelligent+Diagnosis+for+Internet+of+Medical+Things+%28IoMT%29+Applications&rft.jtitle=Information+%28Basel%29&rft.au=Amna+Iqbal&rft.au=Muhammad+Arfan+Jaffar&rft.au=Rashid+Jahangir&rft.date=2024-08-01&rft.pub=MDPI+AG&rft.eissn=2078-2489&rft.volume=15&rft.issue=8&rft.spage=489&rft_id=info:doi/10.3390%2Finfo15080489&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_e89ab5c70b2b41e3b3e332028f18aeb7 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2078-2489&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2078-2489&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2078-2489&client=summon |