Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence.
Xiang BaiHanchen WangLiya MaYongchao XuJiefeng GanZiwei FanFan YangKe MaJiehua YangSong BaiChang ShuXinyu ZouRenhao HuangChangzheng ZhangXiaowu LiuDandan TuChuou XuWenqing ZhangXi WangAnguo ChenYu ZengDehua YangMing-Wei WangNagaraj HolalkereNeil J. HalinIhab R. KamelJia WuXuehua PengXiang WangJianbo ShaoPattanasak MongkolwatJianjun ZhangWeiyang LiuMichael RobertsZhongzhao TengLucian BeerLorena Escudero SanchezEvis SalaDaniel L. RubinAdrian WellerJoan LasenbyChuansheng ZhengJianming WangZhen LiCarola SchönliebTian XiaPublished in: Nat. Mach. Intell. (2021)
Keyphrases
- privacy preserving
- artificial intelligence
- vertically partitioned data
- privacy preserving data mining
- privacy preservation
- private information
- data privacy
- horizontally partitioned data
- privacy sensitive
- multi party
- record linkage
- privacy protection
- preserving privacy
- data transformation
- privacy preserving classification
- data perturbation
- provide efficient solutions
- horizontally partitioned
- partitioned data
- scalar product
- machine learning
- privacy issues
- personal data
- sensitive information
- privacy requirements
- private data
- sensitive data
- naive bayesian classification
- privacy concerns
- knn