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Artificial Intelligence in Healthcare and Education / Machine Learning in Healthcare / Sepsis Diagnosis and Treatment · Journal article
Frontiers in Cellular and Infection Microbiology · August 13, 2026
A consensus or society position rather than new primary data.
This is a narrative review that surveys recent advances in AI applications for prevention, diagnosis, and treatment of infections in older adults, synthesizing conceptual and empirical literature across multiple domains. The source does not report original empirical results, controlled comparisons, or effect sizes; it presents a landscape assessment and identifies AI as a potential complement to traditional care without quantifying clinical benefit.
Narrative review. Older adults (geriatric population) with infectious diseases.
AI applications identified across five domains: early detection of clinical deterioration, rapid and etiologically precise diagnosis, individualized therapeutic optimization, antimicrobial stewardship, and accelerated discovery of novel antimicrobials. Review frames age-related immunosenescence, inflammaging, organ dysfunction, comorbidities, and atypical infection presentation as key determinants affecting older adults' infection susceptibility.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
This review offers clinicians and researchers a conceptual framework for considering AI as an adjunct to conventional infection management in older adults, but does not provide evidence-based estimates of impact on specific clinical outcomes or patient safety metrics.
A narrative review synthesizing current knowledge on AI applications in geriatric infection management, offering conceptual framework and prospects rather than empirical evidence of clinical efficacy.
As stated by the source record.
This review offers clinicians and researchers a conceptual framework for considering AI as an adjunct to conventional infection management in older adults, but does not provide evidence-based estimates of impact on specific clinical outcomes or patient safety metrics.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
What is missing. This record has no reported figures. That is a gap in the analysis, not a judgement about the study.
Background As global population aging accelerates, infectious diseases in older adults have emerged as a growing public health burden with substantial clinical, economic, and societal implications. The rapid advancement of artificial intelligence (AI) offers a transformative opportunity to enhance the management of infections in this vulnerable population. Methods This review delineates key determinants specific to geriatrics that influence infection susceptibility and atypical presentation, including age-related organ dysfunction, immunosenescence, inflammaging, chronic comorbidities, and psychosocial factors, and summarizes the recent advances in AI applications across the management for infectious diseases in older adults. Results AI has made significant progress in the prevention, diagnosis, and treatment of infectious diseases in older adults: early detection of clinical deterioration, rapid and etiologically precise diagnosis, individualized therapeutic optimization, AI-facilitated antimicrobial stewardship, and accelerated discovery of novel antimicrobial strategies. Conclusion AI shows great potential in helping prevent, diagnose, and treat infections in older adults, and represents a promising complement to traditional care approaches.
Taken from the source record, never inferred. Follow any of these and new work involving them reaches your briefing.