Titlebook: Health Information Science; 11th International C Agma Traina,Hua Wang,Lu Chen Conference proceedings 2022 The Editor(s) (if applicable) and

優(yōu)雅

Zeyu Wang,Huiying Zhao,Peng Ren,Yuxi Zhou,Ming Sheng

HPA533

Qi Xiao,Wenkui Zheng,Chenyu Mao,Wei Hou,Hao Lan,Daojun Han,Yang Duan,Peng Ren,Ming Sheng

hallow

Peng Ren,Xingyue Liu,Shuxin Zheng,Lijun Liao,Xin Li,Ligong Lu,Xia Wang,Ruoyu Wang,Ming Sheng

薄荷醇

Shuang Ding,Chenyu Mao,Wenkui Zheng,Qi Xiao,Yitao Wu

Innocence

設(shè)想

Long Yin Guo,Lin Xia,Xin Yi Huang,Yu Xin Fu,Xin Yi Li,Si Chen Zhou,Chao Zhao,Bing Xiang Yang

canonical

Detection of Obsessive-Compulsive Disorder in Australian Children and Adolescents Using Machine Learas been evaluated on the YMM dataset using three of the most optimal algorithms, including Random Forest (RF), Decision Tree (DT), and Gaussian Na?ve Bayes (GaussianNB). GaussianNB outperformed all other methods in classifying OCD with 91% accuracy, 76% precision, and 96% specificity, despite signif

節(jié)約

Gustatory

HGCL: Heterogeneous Graph Contrastive Learning for?Traditional Chinese Medicine Prescription Generatlity of node representations for several downstream tasks such as node classification, prescription generation, etc. We conduct extensive experiments on three real TCM clinical datasets, demonstrating significant improvement over state-of-the-art methods, even though some of which are fully unsuperv

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