FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4323928626> ?p ?o ?g. }

• W4323928626 abstract "The determination of a treatment plan for a target patient with tumor is a difficult problem due to the existence of heterogeneity in patients' responses, incomplete information about tumor states, and asymmetric knowledge between doctors and patients, and so on. In this paper, a method for quantitative risk analysis of treatment plans for patients with tumor is proposed. To reduce the impacts of the heterogeneity in patients' responses on analysis results, the method conducts risk analysis by mining historical similar patients from Electronic Health Records (EHRs) in multiple hospitals using federated learning (FL). For this, the Recursive Feature Elimination based on the Support Vector Machine (SVM) and Deep Learning Important FeaTures (DeepLIFT) are extended into the FL framework to select key features and determine key feature weights for identifying historical similar patients. Then, in the database of each collaborative hospital, the similarities between the target patient and all historical patients are calculated, and the historical similar patients are determined. According to the statistics of tumor states and treatment outcomes of historical similar patients in all collaborative hospitals, the related data (including the probabilities of different tumor states and possible outcomes of different treatment plans) for risk analysis of the alternative treatment plans can be obtained, which can eliminate the asymmetric knowledge between doctors and patients. The related data are valuable for the doctor and patient to make their decisions. Experimental studies have been conducted to verify the feasibility and effectiveness of the proposed method." @default.
• W4323928626 created "2023-03-12" @default.
• W4323928626 creator A5042831653 @default.
• W4323928626 creator A5066468012 @default.
• W4323928626 date "2023-03-11" @default.
• W4323928626 modified "2023-10-17" @default.
• W4323928626 title "Quantitative risk analysis of treatment plans for patients with tumor by mining historical similar patients from electronic health records using federated learning" @default.
• W4323928626 cites W1632122487 @default.
• W4323928626 cites W2013293739 @default.
• W4323928626 cites W2093065590 @default.
• W4323928626 cites W2093385096 @default.
• W4323928626 cites W2096210342 @default.
• W4323928626 cites W2101393389 @default.
• W4323928626 cites W2112979829 @default.
• W4323928626 cites W2143426320 @default.
• W4323928626 cites W2169281690 @default.
• W4323928626 cites W2183890563 @default.
• W4323928626 cites W2235160132 @default.
• W4323928626 cites W2311599690 @default.
• W4323928626 cites W2770027889 @default.
• W4323928626 cites W2783522756 @default.
• W4323928626 cites W2792374194 @default.
• W4323928626 cites W2797401892 @default.
• W4323928626 cites W2800040729 @default.
• W4323928626 cites W2893405045 @default.
• W4323928626 cites W2912213068 @default.
• W4323928626 cites W2933897566 @default.
• W4323928626 cites W2972882814 @default.
• W4323928626 cites W2974429275 @default.
• W4323928626 cites W2977072935 @default.
• W4323928626 cites W2977797911 @default.
• W4323928626 cites W2979571639 @default.
• W4323928626 cites W2979637109 @default.
• W4323928626 cites W3015043285 @default.
• W4323928626 cites W3018464563 @default.
• W4323928626 cites W3027889410 @default.
• W4323928626 cites W3033511014 @default.
• W4323928626 cites W3045674654 @default.
• W4323928626 cites W3064112253 @default.
• W4323928626 cites W3086809868 @default.
• W4323928626 cites W3087782143 @default.
• W4323928626 cites W3093606573 @default.
• W4323928626 cites W3097158220 @default.
• W4323928626 cites W3106805434 @default.
• W4323928626 cites W3113308842 @default.
• W4323928626 cites W3123459983 @default.
• W4323928626 cites W3134285077 @default.
• W4323928626 cites W3135716277 @default.
• W4323928626 cites W3137510859 @default.
• W4323928626 cites W3147142721 @default.
• W4323928626 cites W3150684546 @default.
• W4323928626 cites W3160371670 @default.
• W4323928626 cites W3164193355 @default.
• W4323928626 cites W3164712068 @default.
• W4323928626 cites W3165750456 @default.
• W4323928626 cites W3168162999 @default.
• W4323928626 cites W3183440675 @default.
• W4323928626 cites W3185162399 @default.
• W4323928626 cites W3186401068 @default.
• W4323928626 cites W3191685120 @default.
• W4323928626 cites W3197552266 @default.
• W4323928626 cites W3199772305 @default.
• W4323928626 cites W3200840849 @default.
• W4323928626 cites W3206144059 @default.
• W4323928626 cites W3210782205 @default.
• W4323928626 cites W3213704721 @default.
• W4323928626 cites W3217644914 @default.
• W4323928626 cites W4200624380 @default.
• W4323928626 cites W4205999744 @default.
• W4323928626 cites W4211121451 @default.
• W4323928626 cites W4211133582 @default.
• W4323928626 cites W4214841549 @default.
• W4323928626 cites W4220757123 @default.
• W4323928626 cites W4224109353 @default.
• W4323928626 cites W4226082367 @default.
• W4323928626 cites W4242669880 @default.
• W4323928626 cites W4281638103 @default.
• W4323928626 cites W4289236186 @default.
• W4323928626 doi "https://doi.org/10.1111/risa.14124" @default.
• W4323928626 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36906293" @default.
• W4323928626 hasPublicationYear "2023" @default.
• W4323928626 type Work @default.
• W4323928626 citedByCount "0" @default.
• W4323928626 crossrefType "journal-article" @default.
• W4323928626 hasAuthorship W4323928626A5042831653 @default.
• W4323928626 hasAuthorship W4323928626A5066468012 @default.
• W4323928626 hasConcept C119857082 @default.
• W4323928626 hasConcept C12267149 @default.
• W4323928626 hasConcept C124101348 @default.
• W4323928626 hasConcept C138885662 @default.
• W4323928626 hasConcept C154945302 @default.
• W4323928626 hasConcept C160735492 @default.
• W4323928626 hasConcept C166957645 @default.
• W4323928626 hasConcept C17744445 @default.
• W4323928626 hasConcept C199539241 @default.
• W4323928626 hasConcept C205649164 @default.
• W4323928626 hasConcept C26517878 @default.
• W4323928626 hasConcept C2776401178 @default.
• W4323928626 hasConcept C2776505523 @default.
• W4323928626 hasConcept C3019952477 @default.

• next