Acute on chronic liver failure: prognostic models and artificial intelligence applications
Phillip J Gary1,2, Amos Lal1,2, Douglas A Simonetto3
1Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Hepatology Communications
|March 27, 2023
Summary
Artificial intelligence (AI) offers promising tools for managing acute on chronic liver failure (ACLF), potentially improving patient outcomes and understanding disease mechanisms. Further research is needed to validate AI benefits and address ethical considerations in ACLF patient care.
Area of Science:
- Medical Informatics
- Hepatology
- Artificial Intelligence
Background:
- Acute on chronic liver failure (ACLF) presents significant challenges, including high mortality and frequent readmissions.
- Current understanding and management of ACLF are limited by definitional issues and lack of prospective data.
- Resource allocation, particularly for organ transplantation, is complex in ACLF patients.
Approach:
- This review explores the application of artificial intelligence (AI), including machine learning and natural language processing, in healthcare.
- AI methods are being investigated for prognostic modeling and understanding ACLF morbidity and mortality.
- The potential of AI to reduce cognitive load and improve patient outcomes is discussed.
Key Points:
- AI demonstrates potential in predicting outcomes and understanding disease mechanisms in ACLF.
- Ethical considerations and the need for proven benefits temper the enthusiasm for AI in ACLF.
- AI's impact on patient-centered outcomes and overall care in ACLF remains under investigation.
Conclusions:
- AI offers novel approaches to enhance the care of critically ill patients with ACLF.
- Further validation and ethical evaluation are crucial for integrating AI into ACLF management.
- AI-driven insights may significantly advance the prognosis and treatment strategies for ACLF.
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