Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients.
Curr Opin Infect Dis
; 36(4): 235-242, 2023 08 01.
Article
em En
| MEDLINE
| ID: mdl-37284773
ABSTRACT
PURPOSE OF REVIEW Immunocompromised patients are at high risk for infection. During the coronavirus disease (COVID-19) pandemic, immunocompromised patients exhibited increased odds of intensive care unit admission and death. Early pathogen identification is essential to mitigating infection related risk in immunocompromised patients. Artificial intelligence (AI) and machine learning (ML) have tremendous appeal to address unmet diagnostic needs. These AI/ML tools often rely on the wealth of data found in healthcare to enhance our ability to identify clinically significant patterns of disease. To this end, our review provides an overview of the current AI/ML landscape as it applies to infectious disease testing with emphasis on immunocompromised patients. RECENT FINDINGS:
Examples include AI/ML for predicting sepsis in high risk burn patients. Likewise, ML is utilized to analyze complex host-response proteomic data to predict respiratory infections including COVID-19. These same approaches have also been applied for pathogen identification of bacteria, viruses, and hard to detect fungal microbes. Future uses of AI/ML may include integration of predictive analytics in point-of-care (POC) testing and data fusion applications.SUMMARY:
Immunocompromised patients are at high risk for infections. AI/ML is transforming infectious disease testing and has great potential to address challenges encountered in the immune compromised population.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Doenças Transmissíveis
/
COVID-19
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Curr Opin Infect Dis
Assunto da revista:
DOENCAS TRANSMISSIVEIS
Ano de publicação:
2023
Tipo de documento:
Article