on a large scale, spanning both an extended time period and the largest sample size to date. Through molecular epidemiological investigations based on genomics, we can directly trace the origin of the pathogen, detecting and monitoring outbreaks of infectious diseases in a timely manner, and ensuring public health safety. In addition, this study also collects a large amount of genomic and antibiotic resistance detection data, which is helpful for phenotype prediction based on genomic sequencing. It enables patients to receive personalized antibiotic treatment quickly, helps doctors select antibiotics more accurately, and contributes to reducing the use of antibiotics and lowering the risk of antibiotic resistance development.
Keyphrases
- acinetobacter baumannii
- multidrug resistant
- public health
- infectious diseases
- drug resistant
- pseudomonas aeruginosa
- end stage renal disease
- gram negative
- copy number
- klebsiella pneumoniae
- ejection fraction
- single cell
- newly diagnosed
- prognostic factors
- chronic kidney disease
- peritoneal dialysis
- machine learning
- escherichia coli
- electronic health record
- patient reported outcomes
- risk assessment
- cystic fibrosis
- single molecule
- patient reported
- deep learning
- smoking cessation
- quantum dots
- data analysis