Evaluation metrics of the models constructed by each algorithm.
<p>Evaluation metrics of the models constructed by each algorithm.</p>
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , , , , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852014630368444416 |
|---|---|
| author | Xiaoyan Yang (259084) |
| author2 | Wenqiang Li (483433) Qin Xiao (487551) Shiyun Du (6242342) Xi Wang (15032) Ying Zhang (40767) Sulian Li (22662396) |
| author2_role | author author author author author author |
| author_facet | Xiaoyan Yang (259084) Wenqiang Li (483433) Qin Xiao (487551) Shiyun Du (6242342) Xi Wang (15032) Ying Zhang (40767) Sulian Li (22662396) |
| author_role | author |
| dc.creator.none.fl_str_mv | Xiaoyan Yang (259084) Wenqiang Li (483433) Qin Xiao (487551) Shiyun Du (6242342) Xi Wang (15032) Ying Zhang (40767) Sulian Li (22662396) |
| dc.date.none.fl_str_mv | 2025-11-21T18:32:33Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0336466.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Evaluation_metrics_of_the_models_constructed_by_each_algorithm_/30677514 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified machine learning algorithms digital health tools automatically flag high analyzing feature importance optimal predictive performance important predictive factors data collection occurring whether constipation occurred auc ), accuracy clinical information system namely logistic regression key risk factors identified using shap model predictive performance construct predictive models logistic regression predictive model clinical data svm ), postoperative constipation knn ), constipation risk clinical utility clinical prevention xlink "> study conducted retrospective analysis provide decision outcome variable nutritional risk nearest neighbors model developed model demonstrated may 2024 making support january 2020 hospital stay game theory femoral fracture elderly patients december 2024 chronic gastritis based approach |
| dc.title.none.fl_str_mv | Evaluation metrics of the models constructed by each algorithm. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Evaluation metrics of the models constructed by each algorithm.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_2aaa398be230ea795cdef544ec7fbe69 |
| identifier_str_mv | 10.1371/journal.pone.0336466.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30677514 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Evaluation metrics of the models constructed by each algorithm.Xiaoyan Yang (259084)Wenqiang Li (483433)Qin Xiao (487551)Shiyun Du (6242342)Xi Wang (15032)Ying Zhang (40767)Sulian Li (22662396)MedicineBiotechnologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmachine learning algorithmsdigital health toolsautomatically flag highanalyzing feature importanceoptimal predictive performanceimportant predictive factorsdata collection occurringwhether constipation occurredauc ), accuracyclinical information systemnamely logistic regressionkey risk factorsidentified using shapmodel predictive performanceconstruct predictive modelslogistic regressionpredictive modelclinical datasvm ),postoperative constipationknn ),constipation riskclinical utilityclinical preventionxlink ">study conductedretrospective analysisprovide decisionoutcome variablenutritional risknearest neighborsmodel developedmodel demonstratedmay 2024making supportjanuary 2020hospital staygame theoryfemoral fractureelderly patientsdecember 2024chronic gastritisbased approach<p>Evaluation metrics of the models constructed by each algorithm.</p>2025-11-21T18:32:33ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0336466.t004https://figshare.com/articles/dataset/Evaluation_metrics_of_the_models_constructed_by_each_algorithm_/30677514CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306775142025-11-21T18:32:33Z |
| spellingShingle | Evaluation metrics of the models constructed by each algorithm. Xiaoyan Yang (259084) Medicine Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified machine learning algorithms digital health tools automatically flag high analyzing feature importance optimal predictive performance important predictive factors data collection occurring whether constipation occurred auc ), accuracy clinical information system namely logistic regression key risk factors identified using shap model predictive performance construct predictive models logistic regression predictive model clinical data svm ), postoperative constipation knn ), constipation risk clinical utility clinical prevention xlink "> study conducted retrospective analysis provide decision outcome variable nutritional risk nearest neighbors model developed model demonstrated may 2024 making support january 2020 hospital stay game theory femoral fracture elderly patients december 2024 chronic gastritis based approach |
| status_str | publishedVersion |
| title | Evaluation metrics of the models constructed by each algorithm. |
| title_full | Evaluation metrics of the models constructed by each algorithm. |
| title_fullStr | Evaluation metrics of the models constructed by each algorithm. |
| title_full_unstemmed | Evaluation metrics of the models constructed by each algorithm. |
| title_short | Evaluation metrics of the models constructed by each algorithm. |
| title_sort | Evaluation metrics of the models constructed by each algorithm. |
| topic | Medicine Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified machine learning algorithms digital health tools automatically flag high analyzing feature importance optimal predictive performance important predictive factors data collection occurring whether constipation occurred auc ), accuracy clinical information system namely logistic regression key risk factors identified using shap model predictive performance construct predictive models logistic regression predictive model clinical data svm ), postoperative constipation knn ), constipation risk clinical utility clinical prevention xlink "> study conducted retrospective analysis provide decision outcome variable nutritional risk nearest neighbors model developed model demonstrated may 2024 making support january 2020 hospital stay game theory femoral fracture elderly patients december 2024 chronic gastritis based approach |