Matches in SemOpenAlex for { <https://semopenalex.org/work/W4214640376> ?p ?o ?g. }
- W4214640376 endingPage "2500" @default.
- W4214640376 startingPage "2500" @default.
- W4214640376 abstract "The benefits and drawbacks of various technologies, as well as the scope of their application, are thoroughly discussed. The use of anonymity technology and differential privacy in data collection can aid in the prevention of attacks based on background knowledge gleaned from data integration and fusion. The majority of medical big data are stored on a cloud computing platform during the storage stage. To ensure the confidentiality and integrity of the information stored, encryption and auditing procedures are frequently used. Access control mechanisms are mostly used during the data sharing stage to regulate the objects that have access to the data. The privacy protection of medical and health big data is carried out under the supervision of machine learning during the data analysis stage. Finally, acceptable ideas are put forward from the management level as a result of the general privacy protection concerns that exist throughout the life cycle of medical big data throughout the industry." @default.
- W4214640376 created "2022-03-02" @default.
- W4214640376 creator A5015240056 @default.
- W4214640376 creator A5026196217 @default.
- W4214640376 creator A5031472760 @default.
- W4214640376 creator A5032373930 @default.
- W4214640376 creator A5038241573 @default.
- W4214640376 creator A5044253107 @default.
- W4214640376 creator A5048859324 @default.
- W4214640376 creator A5078484420 @default.
- W4214640376 creator A5078634771 @default.
- W4214640376 date "2022-02-22" @default.
- W4214640376 modified "2023-09-29" @default.
- W4214640376 title "Federated Learning Approach to Protect Healthcare Data over Big Data Scenario" @default.
- W4214640376 cites W1964803288 @default.
- W4214640376 cites W2010462324 @default.
- W4214640376 cites W2053381312 @default.
- W4214640376 cites W2078416735 @default.
- W4214640376 cites W2095359667 @default.
- W4214640376 cites W2407534979 @default.
- W4214640376 cites W2483084990 @default.
- W4214640376 cites W2495019408 @default.
- W4214640376 cites W2583855333 @default.
- W4214640376 cites W2583964134 @default.
- W4214640376 cites W2584479569 @default.
- W4214640376 cites W2591061043 @default.
- W4214640376 cites W2779309941 @default.
- W4214640376 cites W2783221117 @default.
- W4214640376 cites W2903567470 @default.
- W4214640376 cites W2912213068 @default.
- W4214640376 cites W2915360108 @default.
- W4214640376 cites W2997048546 @default.
- W4214640376 cites W3109375702 @default.
- W4214640376 cites W3110422761 @default.
- W4214640376 cites W3113695388 @default.
- W4214640376 cites W3122257830 @default.
- W4214640376 cites W3133693093 @default.
- W4214640376 cites W3134164430 @default.
- W4214640376 cites W3135894856 @default.
- W4214640376 cites W3179626308 @default.
- W4214640376 cites W3192530604 @default.
- W4214640376 cites W3196030666 @default.
- W4214640376 cites W3201491846 @default.
- W4214640376 cites W3204099090 @default.
- W4214640376 cites W3204954480 @default.
- W4214640376 cites W3208360369 @default.
- W4214640376 cites W3209315923 @default.
- W4214640376 cites W3210935118 @default.
- W4214640376 cites W3213802103 @default.
- W4214640376 cites W3215520248 @default.
- W4214640376 cites W3215729113 @default.
- W4214640376 cites W4200009931 @default.
- W4214640376 cites W4200200775 @default.
- W4214640376 cites W4200415606 @default.
- W4214640376 cites W4200464355 @default.
- W4214640376 cites W4200529309 @default.
- W4214640376 cites W4205737054 @default.
- W4214640376 doi "https://doi.org/10.3390/su14052500" @default.
- W4214640376 hasPublicationYear "2022" @default.
- W4214640376 type Work @default.
- W4214640376 citedByCount "22" @default.
- W4214640376 countsByYear W42146403762022 @default.
- W4214640376 countsByYear W42146403762023 @default.
- W4214640376 crossrefType "journal-article" @default.
- W4214640376 hasAuthorship W4214640376A5015240056 @default.
- W4214640376 hasAuthorship W4214640376A5026196217 @default.
- W4214640376 hasAuthorship W4214640376A5031472760 @default.
- W4214640376 hasAuthorship W4214640376A5032373930 @default.
- W4214640376 hasAuthorship W4214640376A5038241573 @default.
- W4214640376 hasAuthorship W4214640376A5044253107 @default.
- W4214640376 hasAuthorship W4214640376A5048859324 @default.
- W4214640376 hasAuthorship W4214640376A5078484420 @default.
- W4214640376 hasAuthorship W4214640376A5078634771 @default.
- W4214640376 hasBestOaLocation W42146403761 @default.
- W4214640376 hasConcept C111919701 @default.
- W4214640376 hasConcept C121955636 @default.
- W4214640376 hasConcept C123201435 @default.
- W4214640376 hasConcept C124101348 @default.
- W4214640376 hasConcept C142724271 @default.
- W4214640376 hasConcept C144133560 @default.
- W4214640376 hasConcept C148730421 @default.
- W4214640376 hasConcept C160735492 @default.
- W4214640376 hasConcept C162324750 @default.
- W4214640376 hasConcept C162853370 @default.
- W4214640376 hasConcept C1668388 @default.
- W4214640376 hasConcept C176217482 @default.
- W4214640376 hasConcept C178005623 @default.
- W4214640376 hasConcept C196879817 @default.
- W4214640376 hasConcept C199360897 @default.
- W4214640376 hasConcept C199521495 @default.
- W4214640376 hasConcept C204787440 @default.
- W4214640376 hasConcept C24756922 @default.
- W4214640376 hasConcept C2522767166 @default.
- W4214640376 hasConcept C2778012447 @default.
- W4214640376 hasConcept C2779965156 @default.
- W4214640376 hasConcept C33762810 @default.
- W4214640376 hasConcept C38652104 @default.
- W4214640376 hasConcept C41008148 @default.