Performance of the classification models before applying dual-GAN.
<p>Performance of the classification models before applying dual-GAN.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852020783820308480 |
|---|---|
| author | Priyanka Roy (14580479) |
| author2 | Fahim Mohammad Sadique Srijon (19751363) Pankaj Bhowmik (6002078) |
| author2_role | author author |
| author_facet | Priyanka Roy (14580479) Fahim Mohammad Sadique Srijon (19751363) Pankaj Bhowmik (6002078) |
| author_role | author |
| dc.creator.none.fl_str_mv | Priyanka Roy (14580479) Fahim Mohammad Sadique Srijon (19751363) Pankaj Bhowmik (6002078) |
| dc.date.none.fl_str_mv | 2025-05-05T16:50:52Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0310748.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Performance_of_the_classification_models_before_applying_dual-GAN_/28931603 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Cell Biology Genetics Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified world every year significantly improved precision significant class imbalance prioritizing stable performance planning treatment early medical image datasets leading diseases imposing handling class imbalance deep learning models brain tumor classification medical imaging data highly imbalanced data feature extraction techniques overall healthcare process overall classification process improving patient outcomes explainable ensemble approach gan mechanism facilitates classification process explainable ensemble gan mechanism techniques aid proposed mechanism ml techniques overall accuracy study proposes study presents study focuses specifically designed shown promise score demonstrate research identifies reliable model proposed pipeline original quality mri scans informative features incorporating grad frequently affected crucial role contributing parts clinical diagnosis benchmark ml based pipeline 15 %. |
| dc.title.none.fl_str_mv | Performance of the classification models before applying dual-GAN. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Performance of the classification models before applying dual-GAN.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_28eca2eb6882fd0b23ebfdb6cbee9eda |
| identifier_str_mv | 10.1371/journal.pone.0310748.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28931603 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Performance of the classification models before applying dual-GAN.Priyanka Roy (14580479)Fahim Mohammad Sadique Srijon (19751363)Pankaj Bhowmik (6002078)MedicineCell BiologyGeneticsCancerSpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedworld every yearsignificantly improved precisionsignificant class imbalanceprioritizing stable performanceplanning treatment earlymedical image datasetsleading diseases imposinghandling class imbalancedeep learning modelsbrain tumor classificationmedical imaging datahighly imbalanced datafeature extraction techniquesoverall healthcare processoverall classification processimproving patient outcomesexplainable ensemble approachgan mechanism facilitatesclassification processexplainable ensemblegan mechanismtechniques aidproposed mechanismml techniquesoverall accuracystudy proposesstudy presentsstudy focusesspecifically designedshown promisescore demonstrateresearch identifiesreliable modelproposed pipelineoriginal qualitymri scansinformative featuresincorporating gradfrequently affectedcrucial rolecontributing partsclinical diagnosisbenchmark mlbased pipeline15 %.<p>Performance of the classification models before applying dual-GAN.</p>2025-05-05T16:50:52ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0310748.t004https://figshare.com/articles/dataset/Performance_of_the_classification_models_before_applying_dual-GAN_/28931603CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/289316032025-05-05T16:50:52Z |
| spellingShingle | Performance of the classification models before applying dual-GAN. Priyanka Roy (14580479) Medicine Cell Biology Genetics Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified world every year significantly improved precision significant class imbalance prioritizing stable performance planning treatment early medical image datasets leading diseases imposing handling class imbalance deep learning models brain tumor classification medical imaging data highly imbalanced data feature extraction techniques overall healthcare process overall classification process improving patient outcomes explainable ensemble approach gan mechanism facilitates classification process explainable ensemble gan mechanism techniques aid proposed mechanism ml techniques overall accuracy study proposes study presents study focuses specifically designed shown promise score demonstrate research identifies reliable model proposed pipeline original quality mri scans informative features incorporating grad frequently affected crucial role contributing parts clinical diagnosis benchmark ml based pipeline 15 %. |
| status_str | publishedVersion |
| title | Performance of the classification models before applying dual-GAN. |
| title_full | Performance of the classification models before applying dual-GAN. |
| title_fullStr | Performance of the classification models before applying dual-GAN. |
| title_full_unstemmed | Performance of the classification models before applying dual-GAN. |
| title_short | Performance of the classification models before applying dual-GAN. |
| title_sort | Performance of the classification models before applying dual-GAN. |
| topic | Medicine Cell Biology Genetics Cancer Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified world every year significantly improved precision significant class imbalance prioritizing stable performance planning treatment early medical image datasets leading diseases imposing handling class imbalance deep learning models brain tumor classification medical imaging data highly imbalanced data feature extraction techniques overall healthcare process overall classification process improving patient outcomes explainable ensemble approach gan mechanism facilitates classification process explainable ensemble gan mechanism techniques aid proposed mechanism ml techniques overall accuracy study proposes study presents study focuses specifically designed shown promise score demonstrate research identifies reliable model proposed pipeline original quality mri scans informative features incorporating grad frequently affected crucial role contributing parts clinical diagnosis benchmark ml based pipeline 15 %. |