ReviewCritical care (London, England)2025
Transforming sepsis management: AI-driven innovations in early detection and tailored therapies.
Review in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Recent advances in screening, diagnosis, prognosis and personalized treatment of sepsis.European journal of microbiology & immunology · 2026Review
- Systems Bioengineering of Septic Shock Metabolism: Citrulline, β-Hydroxybutyrate and Plasma Biomarker-Based Phenotyping.Biomolecules · 2026Review
- Artificial Intelligence in Pharmaceutical Care:Saudi medical journal · 2026Review
- Using interpretable machine learning to analyze the trajectory changes of serum albumin to predict the mortality rate of sepsis: a cohort study based on MIMIC-IV.BMC infectious diseases · 2026Article
- Explainable Artificial Intelligence in Critical Care Nursing: A Discussion Paper.Nursing in critical care · 2026Article
- Validation is not enough: Longitudinal evidence of post-deployment fragility in clinical AI systems.PLOS digital health · 2026Article
- Artificial Intelligence in Infectious Disease Care: Selected Applications in Tuberculosis, Sepsis, and Antimicrobial Stewardship.Diagnostics (Basel, Switzerland) · 2026Review
- An autonomous AI agent for knowledge and data cooperation in ED clinical decision support.NPJ digital medicine · 2026Article
- Review
- Nanomaterial-nucleic acid probe synergy: accelerating rapid pathogen detection and antimicrobial susceptibility testing in bloodstream infections.Folia microbiologica · 2026Review
- Artificial Intelligence Virtual Organoids (AIVOs).Bioactive materials · 2026Review
- Conformance-Aware Predictive Process Monitoring for Early Detection of Sepsis Deterioration Using Incomplete Care Pathways.Journal of clinical medicine · 2026Article
- Explainable Artificial Intelligence in Healthcare: Current Landscape, Challenges, and Future Directions.Health science reports · 2026Review
- Narrative review on microbiota and sepsis: the host's betrayal?Internal and emergency medicine · 2026Review
- The next frontier in sepsis: connected ICU data for real-world clinical decision making.Intensive care medicine · 2026Review
- Artificial Intelligence Drives Advances in Multi-Omics Analysis and Precision Medicine for Sepsis.Biomedicines · 2026Review
- Hyper-inflammation and immunosuppression: redefining sepsis therapy using modern approaches.Frontiers in pharmacology · 2026Review
- Cell death in sepsis: unveiling new perspectives on organ dysfunction.Frontiers in cell and developmental biology · 2026Review
- Thirty-five years of evolving inflammatory paradigms in sepsis (1991-2025): a comprehensive mapping of immune dysregulation research, anti-inflammatory targets, and translational barriers.Frontiers in immunology · 2026Article
- Multi-omic and computational approaches for biomarker discovery and clinical translation in pediatric sepsis.Frontiers in pharmacology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sepsis remains a leading cause of mortality worldwide, driven by its clinical complexity and delayed recognition. Artificial intelligence (AI) offers promising solutions to improve sepsis care through earlier detection, risk stratification, and personalized treatment strategies. Key applications include AI-driven early warning systems, subphenotyping based on clinical and biological data, and decision support tools that adapt to real-time patient information. The integration of diverse data types, such as structured clinical data, unstructured notes, waveform signals, and molecular biomarkers, enhances the precision and timeliness of interventions. However, challenges such as algorithmic bias, limited external validation, data quality issues, and ethical considerations continue to hinder clinical implementation. Future directions focus on real-time model adaptation, multi-omics integration, and the development of generalist medical AI capable of personalized recommendations. Successfully addressing these barriers is essential for AI to deliver on its potential to transform sepsis management and support the transition toward precision-driven critical care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.