Experimental hardware and software environment.

Experimental hardware and software environment.

<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. However, these statistical methods require collecting data from the entire research area, which consumes a significant amount of manpowe...

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Bibliographic Details
Main Author: Xing Chen (140292) (author)
Other Authors: Na Zhang (333280) (author), Xiaohui Yang (352345) (author), Chunyan Wang (306606) (author), Qi Na (12691231) (author), Tianyun Luan (20314628) (author), Wendi Zhu (15369385) (author), Chenjie Zhang (11328211) (author), Chao Yang (174810) (author)
Published: 2024
Subjects:
Genetics
Biotechnology
Science Policy
Infectious Diseases
Plant Biology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
strong learning ability
public health authorities
generative adversarial networks
experimental results demonstrate
entire research area
two common algorithms
algorithm takes advantage
corresponding data type
missing data samples
discrete missing data
evident practical significance
data matrix filled
real data distribution
missing data filling
missing data
real data
data distribution
proposed algorithm
filling algorithms
attribute matrix
published data
generated data
filling data
data integration
distribution deviation
xlink ">
training stability
timely analysis
significant amount
reliable knowledge
network structures
medical institutions
material resources
loss function
large number
higher accuracy
fewer errors
ensuring consistency
downstream tasks
directly convert
daily life
cardiac disease
approach establishes
ambiguous meaning
actual meaning
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